health data phd

Health Sciences Informatics, PhD

School of medicine.

The Ph.D. in Health Sciences Informatics offers the opportunity to participate in ground-breaking research projects in clinical informatics and data science at one of the world’s finest biomedical research institutions. In keeping with the traditions of the Johns Hopkins University and the Johns Hopkins Hospital, the Ph.D. program seeks excellence and commitment in its students to further the prevention and management of disease through the continued exploration and development of health informatics, health IT, and data science. Resources include a highly collaborative clinical faculty committed to research at the patient, provider, and system levels. The admissions process will be highly selective and finely calibrated to complement the expertise of faculty mentors.    

Areas of research:

• Clinical Decision Support
• Global Health Informatics
• Health Information Exchange (HIE)
• Human Computer Interaction
• Multi-Center Real World Data
• Patient Quality & Safety
• Population Health Analytics
• Precision Medicine Analytics
• Standard Terminologies
• Telemedicine
• Translational Bioinformatics

Individuals wishing to prepare themselves for careers as independent researchers in health sciences informatics, with applications experience in informatics across the entire health/healthcare life cycle, should apply for admission to the doctoral program.

Admission Criteria

Applicants with the following types of degrees and qualifications will be considered:

• BA or BS, with relevant technical and quantitative competencies and a record of scientific accomplishment as an undergraduate; 
• BA or BS, with relevant technical and quantitative competencies and a minimum of five years professional experience in a relevant field (e.g., biomedical research, data science, public health, etc.); or
• MA, MS, MPH, MLIS, MD, PhD, or other terminal degree, with relevant technical and quantitative competencies

Relevant fields include: medicine, dentistry, veterinary science, nursing, ancillary clinical sciences, public health, librarianship, biomedical science, bioengineering and pharmaceutical sciences, and computer and information science. An undergraduate minor or major in information or computer science is highly desirable.

The application is made available online through Johns Hopkins School of Medicine's website . Please note that paper applications are no longer accepted. The supporting documents listed below must be received by the SOM admissions office by December 15 of the following year. Applications will not be reviewed until they are complete and we have all supporting letters and documentation.

• Curriculum Vitae (including list of peer-reviewed publications and scientific presentations)
• Three Letters of Recommendation
• Statement of Purpose
• Official Transcripts from undergraduate and any graduate studies
• Certification of terminal degree
• You are also encouraged to submit a portfolio of published research, writing samples, and/or samples of website or system development

Please track submission of supporting documentation through the SLATE admissions portal.

If you have questions about your qualifications for this program, please contact [email protected]

Program Requirements

The PhD curriculum will be highly customized based on the student's background and needs. Specific courses and milestones will be developed in partnership with the student's advisor and the PhD Program Director.

The proposed curriculum is founded on four high-level principles:

• Achieving a balance between theory and research, and between breadth and depth of knowledge
• Creating a curriculum around student needs, background, and goals
• Teaching and research excellence
• Modeling professional behavior locally and nationally.

Individualized curriculum plans will be developed to build proficiencies in the following areas:

• Foundations of biomedical informatics: e.g., lifecycle of information systems, decision support
• Information and computer science: e.g., software engineering, programming languages, design and analysis of algorithms, data structures.
• Research methodology: research design, epidemiology, and systems evaluation; mathematics for computer science (discrete mathematics, probability theory), mathematical statistics, applied statistics, mathematics for statistics (linear algebra, sampling theory, statistical inference theory, probability); ethnographic methods.
• Implementation sciences: methods from the social sciences (e.g., organizational behavior and management, evaluation, ethics, health policy, communication, cognitive learning sciences, psychology, and sociological knowledge and methods), health economics, evidence-based practice, safety, quality.
• Specific informatics domains: clinical informatics, public health informatics, analytics
• Practical experience: experience in informatics research, experience with health information technology.

Basic Requirements & Credit Distribution

• 15 "core" quarter credits (5 courses)
• 8 quarter credits of Student Seminar & Grand Rounds
• 60 elective quarter credits
• 6 quarter credits practicum/research rotation
• 36 mentored research quarter credits (12 in year 1, 24 in year 2)
• Research Ethics

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Health Data Science

• Entry year 2024
• Duration Full time 36 Months

The PhD in Health Data Science provides research training in developing applied informatic and analytic approaches to data within health-related subjects such as medicine and the biomedical, biotechnological, and bioengineering sciences.

You will join the programme with a supervisory panel composed of academics working in health data science more broadly. Throughout the programme, and particularly during your first year, you will be encouraged to engage in training opportunities at Lancaster and elsewhere to develop both your research skills and subject-specific knowledge and abilities. Throughout your studies, you will focus on novel scientific research, developing best practice in interpreting and communicating new scientific methods and findings.

Your department

• Lancaster Medical School Faculty of Health and Medicine
• Telephone +44 (0)1524 592032

Entry requirements

Academic requirements.

2:1 Hons degree (UK or equivalent) in a relevant subject.

We may also consider non-standard applicants, please contact us for information.

If you have studied outside of the UK, we would advise you to check our list of international qualifications before submitting your application.

Additional Requirements

As part of your application you will also need to provide a viable research proposal. Guidance for writing a research proposal can be found on our writing a research proposal webpage.

English Language Requirements

We may ask you to provide a recognised English language qualification, dependent upon your nationality and where you have studied previously.

We normally require an IELTS (Academic) Test with an overall score of at least 6.5, and a minimum of 5.5 in each element of the test. We also consider other English language qualifications .

If your score is below our requirements, you may be eligible for one of our pre-sessional English language programmes .

Contact: Admissions Team +44 (0) 1524 592032 or email [email protected]

Fees and funding

The tuition fee for students with home fee status is set in line with the standard fee stipend provided by the UK Research Councils. The fee stipend for 2024/25 has not been set. For reference, the fee stipend for 2023/24 was full-time £4,712.

The international fee for new entrants in 2024/25 is full-time £26,490.

Depending on the nature of the research project, an additional programme cost may be charged. This additional fee will contribute towards the costs incurred on specific research projects. These costs could include purchasing specialist consumables, equipment access charges, fieldwork expenses and payments for transcription/translation services.  Normally any additional charge will not exceed a maximum of £9,720 but this could be increased in exceptional circumstances.

Applicants will be notified of any specific additional programme cost when the offer of a place is made.

General fees and funding information

There may be extra costs related to your course for items such as books, stationery, printing, photocopying, binding and general subsistence on trips and visits. Following graduation, you may need to pay a subscription to a professional body for some chosen careers.

Specific additional costs for studying at Lancaster are listed below.

College fees

Lancaster is proud to be one of only a handful of UK universities to have a collegiate system. Every student belongs to a college, and all students pay a small College Membership Fee  which supports the running of college events and activities. Students on some distance-learning courses are not liable to pay a college fee.

For students starting in 2023 and 2024, the fee is £40 for undergraduates and research students and £15 for students on one-year courses. Fees for students starting in 2025 have not yet been set.

Computer equipment and internet access

To support your studies, you will also require access to a computer, along with reliable internet access. You will be able to access a range of software and services from a Windows, Mac, Chromebook or Linux device. For certain degree programmes, you may need a specific device, or we may provide you with a laptop and appropriate software - details of which will be available on relevant programme pages. A dedicated  IT support helpdesk  is available in the event of any problems.

The University provides limited financial support to assist students who do not have the required IT equipment or broadband support in place.

For most taught postgraduate applications there is a non-refundable application fee of £40. We cannot consider applications until this fee has been paid, as advised on our online secure payment system. There is no application fee for postgraduate research applications.

For some of our courses you will need to pay a deposit to accept your offer and secure your place. We will let you know in your offer letter if a deposit is required and you will be given a deadline date when this is due to be paid.

The fee that you pay will depend on whether you are considered to be a home or international student. Read more about how we assign your  fee status .

If you are studying on a programme of more than one year’s duration, the tuition fees for subsequent years of your programme are likely to increase each year. Read more about  fees in subsequent years .

Scholarships and bursaries

You may be eligible for the following funding opportunities, depending on your fee status and course. You will be automatically considered for our main scholarships and bursaries when you apply, so there's nothing extra that you need to do.

Unfortunately no scholarships and bursaries match your selection, but there are more listed on scholarships and bursaries page.

If you're considering postgraduate research you should look at our funded PhD opportunities .

We also have other, more specialised scholarships and bursaries - such as those for students from specific countries.

Browse Lancaster University's scholarships and bursaries .

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Important Information

The information on this site relates primarily to 2024/2025 entry to the University and every effort has been taken to ensure the information is correct at the time of publication.

The University will use all reasonable effort to deliver the courses as described, but the University reserves the right to make changes to advertised courses. In exceptional circumstances that are beyond the University’s reasonable control (Force Majeure Events), we may need to amend the programmes and provision advertised. In this event, the University will take reasonable steps to minimise the disruption to your studies. If a course is withdrawn or if there are any fundamental changes to your course, we will give you reasonable notice and you will be entitled to request that you are considered for an alternative course or withdraw your application. You are advised to revisit our website for up-to-date course information before you submit your application.

More information on limits to the University’s liability can be found in our legal information .

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We believe in the importance of a strong and productive partnership between our students and staff. In order to ensure your time at Lancaster is a positive experience we have worked with the Students’ Union to articulate this relationship and the standards to which the University and its students aspire. View our Charter and other policies .

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Center for Health Data Science

The Center for Health Data Science leverages data in combination with knowledge across disciplines and places, with the ultimate goal of addressing quality of life and other public health priorities. CHDS enhances interdisciplinary public health research, teaching and practice through leveraging and developing data science methods in conjunction with public health knowledge, frameworks and action as well as with other disciplines such as computer science, urban planning and sociology. CHDS values and promotes pluralistic knowledge discovery and action, such as through cross-border student and faculty exchanges based on long-term relationships, and by working directly with practitioners on the ground to help address community needs.

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Public Health Data Science

The MS in Biostatistics Public Health Data Science Track (MS/PHDS) is designed for students interested in careers as biostatisticians applying statistical methods in health-related research settings. The MS/PHDS Track provides core training in biostatistical theory, methods, and applications, but adds a distinct emphasis on modern approaches to statistical learning, reproducible and transparent code, and data management. It is an appropriate program for students who intend to conclude their studies with the MS degree as well as those who want to pursue a PhD in biostatistics

All MS/PHDS candidates begin their studies in the fall semester. The length of the MS/PHDS program varies with the background, training, and experience of the candidate, but the usual period needed to complete the 36 credit MS/PHDS degree is two years (four semesters). In addition to fulfilling their course work, all MS/PHDS students also complete a one-term practicum and capstone experience.

Competencies

Through a curriculum of 36 credit hours of course work, a practicum, and the capstone experience, the MS/PHDS track provides students with the skills necessary for a career as a public health data scientist and a rigorous grounding in traditional biostatistics.

In addition to achieving the MS in Biostatistics core competencies, students in the PHDS Track gain the following specific competencies in the areas of public health and collaborative research, the foundations of applied data science, teaching biostatistics and biostatistical research. Upon satisfactory completion of the MS/PHDS, graduates will be able to:

Public Health and Collaborative Research

• Formulate and prepare a written statistical plan for analysis of public health research data that clearly reflects the research hypotheses of the proposal in a manner that resonates with both co-investigators and peer reviewers;
• Prepare written summaries of quantitative analyses for journal publication, presentations at scientific meetings, grant applications, and review by regulatory agencies;

Foundations of Applied Data Science

• Develop expertise in one or more statistical software and database management packages (often R and SQL, among others) routinely used by data science professionals;
• Implement a reproducible workflow for data analysis projects, including robust project organization, transparent data management, and reproducible analysis results;
• Develop and execute analysis strategies that use traditional statistical tools or modern approaches to statistical learning, depending on the nature of the scientific questions of interest;
• Identify the uses to which data management can be put in practical statistical analysis, including the establishment of standards for documentation, archiving, auditing, and confidentiality; guidelines for accessibility; security; structural issues; and data cleaning;

Teaching Biostatistics

• Review and illustrate selected principles of study design, probability theory, estimation, hypothesis testing, statistical learning, and data analytic techniques to public health students enrolled in introductory level graduate public health courses; and

Biostatistical Research

• Apply probabilistic, statistical, and data scientific reasoning to structure thinking and solve a wide range of problems in public health.

Course Requirements

MS/PHDS graduates are expected to master the mathematical and biostatistical concepts and techniques presented in the curriculum’s required courses. Each student's program is designed on an individual basis in consultation with a faculty advisor taking into consideration the student's prior educational experience.

Students who have mastered an academic area through previous training may have the corresponding course requirement waived. Some students, such as those with undergraduate majors in statistics or mathematics, may apply to have several courses waived. Students wishing to waive one or more courses must request approval in writing from their advisors and the Director of Academic Programs. These students must still complete a minimum of 36 points to earn the MS/PHDS degree.

Required Courses

Below is the required course work. Students consult their faculty advisors before registering for classes to plan their programs based on their individual background, goals, and the appropriate sequencing of courses. Waiver of any required courses (with prior written approval of their faculty advisor and the Director of Academic Programs) enables students to take other, higher level classes.

*Students who have strong math background and/or have taken basic machine learning methods, can substitute the P8106 Data Science II with P9120 Topics in Statistical Learning and Data Mining I. 

Students choose four or more courses from the list below or from alternatives approved by their academic advisors.

Sample Timeline

Below is a sample timeline for MS/PHDS candidates. Note that course schedules change from year to year, so that class days/times in future years will differ from the sample schedule below; you must check the current course schedule for each year on the course directory page .

Practicum Requirement

One term of practical experience is required of all students, providing educational opportunities that are different from and supplementary to the more academic aspects of the program. The practicum may be fulfilled during the school year or over the summer. Arrangements are made on an individual basis in consultation with faculty advisors who must approve both the proposed practicum project prior to its initiation, and the report submitted at the conclusion of the practicum experience. Students will be required to make a poster presentation at the department’s Annual Practicum Poster Symposium which is held in early May.

Capstone Experience

A formal, culminating experience for the MS degree is required for graduation. The capstone consulting seminar is designed to enable students to demonstrate their ability to integrate their academic studies with the role of biostatistical consultant/collaborator, which will comprise the major portion of their future professional practice.  

As part of the seminar, students are required to attend several sessions of the Biostatistics Consulting Service (BCS). The Consultation Service offers advice on data analysis and appropriate methods of data presentation for publications, and provides design recommendations for public health and clinical research, including preparation of grant proposals. Biostatistics faculty and research staff members conduct all consultation sessions with students observing, modeling, and participating in the consultations.

In the capstone seminar, students present their experience and the statistical issues that emerged in their consultations, developing statistical report writing and presentation skills essential to their professional practice in biomedical and public health research projects.

Paul McCullough Director of Academic Programs Department of Biostatistics Columbia University [email protected]

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Health Data Science Concentration

Course information.

In addition to the existing core and elective courses in the Master of Science or PhD programs, the Health Data Science concentration features four core courses and five elective courses. Some of these courses are part of the current Master of Science program courses and some are new courses designed specifically for the Health Data Science concentration. One of the four core courses replace required courses for the traditional MS degree (BIOS 653: Applied Statistics III – Longitudinal Data Analysis).

Core and Elective Courses

Featured core courses in the Health Data Science concentration

Additional core courses can be found here.

Featured elective courses in the Health Data Science concentration

Course Selection Roadmap

Students' computing skills will be assessed for election of courses from the Health Data Science concentration and other degree core/elective courses. First-year MS students in Biostatistics can access information and advice from the department and faculty to plan their sequence of course selections.  Ongoing PhD students are able to complete this concentration. If they choose this route, some additional coursework is needed in order to meet the requirements of both the PhD and the HDS concentration.

HDS students must complete for their capstone courses (i) all four credits of BIOSTAT 699 and (ii) BIOSTAT 629 (1-2 credits). Biostat 629 will correspond to one or two comprehensive projects on mobile health, electronic health records, imaging data, omics data, etc.

Tables I and II below present two examples of course selections for a student with modest computing skills (e.g. having little knowledge of R programming) and for a student with strong computing skills (e.g. having extensive knowledge and experience in R, C++ and Python programming), respectively.

BIOS 607 is designed to prepare students with computing skills. In this way the Health Data Science concentration is more flexible and inclusive as a professional training program for workforce in health data analytics.

Table I. A possible sequence of course selections by an incoming MS student with modest computing skills, who begins with the three modules of BIOS 607.

Table II. A possible sequence of course selections by a first-year MS student with strong computing skills, who does not take BIOSTAT 607 but begins with BIOSTAT 625.

Note that there is one course (BIOS 653) not included in the curriculum of the Health Data Science concentration that is required by the PhD qualifying exams. Students interested in pursuing a PhD should take 653 in place of an elective the 2nd fall semester. Students already in the PhD program should take BIOS 653 for their qualifying exams.

Admissions Information

Students must be admitted to the Master of Science or PhD program in the University of Michigan School of Public Health's Department of Biostatistics. Once admitted, students will declare their intention to pursue the Health Data Science concentration at the end of their first year, by the end of May.

Have Questions?

For more information about the Health Data Science concentration, contact one of our graduate program coordinators.

Fatma Nedjari

Phone: 734-615-9812 Email: [email protected]

Nicole Fenech

Phone: 734-615-9817 Email: [email protected]  

Frequently Asked Questions

How/when do i apply for this program.

The Health Data Science concentration is not an option in the MS application, and thus there is no application procedure. Interested students should simply declare their intention to complete the Health Data Science concentration by May before their first (Fall) semester at Michigan Public Health by notifying a graduate program coordinator (Fatma Nedjari or Nicole Fenech). Students are encouraged to consult with their academic adviser about Health Data Science course selection.

Will I get in? Is there a cap? Am I automatically in? Are there more prerequisites?

There is no screening or selection procedure. This concentration program is open to all incoming Biostatistics MS students and operated as an automatic enrollment option. Interested students are encouraged to make a decision as soon as they arrive in their first Fall semester since the concentration courses are spread out over two years. As a specific track within the MS program, all Health Data Science courses require the same prerequisites as those in the core courses in the MS program.

When will I know if I get in the concentration program?

You may either notify a graduate program coordinator about your desire to pursue the Health Data Science subplan immediately after you decide to accept your admission offer to the Biostatistics MS program or in the beginning of your first Fall semester. At the stage of enrollment, simply follow the courses required by the Health Data Science concentration.

I have been admitted directly from a bachelor's degree program to the PhD program (or I definitely want to do the PhD program). Am I eligible for this Health Data Science concentration?

Yes, although masters' students interested in applying for the PhD program must be sure to include BIOS 653 (Theory and Application of Longitudinal Data Analysis) in their coursework.

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HDR UK-Turing Wellcome PhD Programme in Health Data Science

This truly outstanding and generously funded four-year programme at top UK universities provides you a pathway to join the UK’s leaders in health data research.

What this unique PhD programme offers you

Four-year programme: An initial foundation year allows students to gain real experience and insight into health data research.

Hosted by leading universities: Our host universities are among the very best in health data research.

Nurturing each student: Our programme aims to identify the particular abilities and interests of each student, and gear their PhD experience to effectively develop them.

Leadership Programme: Students benefit from a bespoke expert-led programme to develop the skills they need to understand, collaborate and influence others.

Generous funding: Students have their tuition fees (UK Home rate), college fees (where applicable), research expenses and travel costs paid and receive an enhanced, tax-free stipend with increases every year. (Y1 outside London: £23,955, Y1 in London: £25,954)

Building networks and experience: We actively support students in building networks and contacts in academia, the NHS and industry as well as taking internships and other opportunities to gain real-world experience. This includes a post-PhD bursary to support your next career step.

Team spirit: Strong relationships are built between our entire cohort of students through joint activities that build a genuine team spirit.

Personal support:  Each student has their own Director of Studies who is an additional point of contact during their time with us. All students are also further supported by the PhD team.

“The PhD programme has enabled me to gain first-hand experience in modern health data science approaches. It’s a truly unrivalled opportunity.”  Steven Wambua

Who is the PhD programme for?

We recruit enthusiastic, talented students who want to use data-driven research to develop and shape the UK’s response to the most complex health challenges of our times.

Applicants must have (or be on track to obtain):

• A first class or 2:1 undergraduate degree in statistics, mathematics, computer / data science, physics or an allied subject  or
• Another undergraduate degree subject and outcome but can demonstrate their suitability for this programme through additional qualifications or research experience.

Active or currently registered health care professionals   are not eligible and should consider the Wellcome PhD Fellowships for Health Professionals .

Applicants also need to meet the following criteria:

• Successful admission to the specified degree programme at one of our partner universities. Students will be expected to meet the admissions requirements of that department and university but do not need to hold the offer at the point of application.
• Two satisfactory academic or relevant references.
• Proof of a legal right to study in the UK or ability to satisfy the current requirements of UK Visa and Immigration.

Training is in-person, hybrid and virtual throughout the first year.

We are committed to a diverse and inclusive research culture . We welcome those who are returning from the workplace, international candidates and everyone underrepresented in STEM and academia. For further details see our FAQs .

We cannot accept applicants who are looking for a part-time PhD or those who are aiming to study whilst continuing to be employed elsewhere.

We aim to accommodate specific needs and personal circumstances. Please make us aware of individual circumstances when applying or contact us directly at  [email protected] . Please note our  applicant privacy notice .

If you have questions or require adjustments to the application process, please contact us below via email or telephone (+44 (0)770 847 8846).

There are no nationality restrictions and international students are able to apply. However, applicants are advised the award only covers fees at the UK/Home level. International students will be required to secure an additional scholarship from Queen’s University Belfast (after receiving a offer from us at interview) to cover the difference between Home and Overseas fees. This will limit the university choices available:

(Please be aware that these are usually highly competitive and will need to be applied for separately in your application to Queen’s University Belfast post-offer. A successful application to the PhD programme does not guarantee a fee waiver or scholarship. We do not accept applications from candidates who are self-funding.)

We are currently only recruiting for Queen’s University Belfast.

These are only initial programmes of study for Year 1. Students may transfer to a new university programme from Year 2 after research projects have been confirmed.

Is this the PhD future for you?

Watch our Applicant Open Day hosted by our current students to find out more about the programme and whether it’s for you.

Applications are currently: Open

There is  one studentship available for October 2024 entry, based at Queen’s University Belfast. Applications are currently accepted through our application portal below:

Begin your application here

Deadline: Sunday 14 April 2024 at 23:59

The application process

Details required:

• Contact details
• Details and transcripts of university qualification(s)
• Any relevant job history
• Answers to personal-statement type questions (250-words maximum for each answer)
• Contact details for two referees
• There is no need to apply to the university, submit a research proposal, provide IELTS scores or contact supervisors at this stage

Submitted applications will first be checked for eligibility and then will undergo a first stage review. This will involve triage by the PhD Team in April 2024 . Successful applicants will be invited to an interview in May 2024 .

After receiving an offer, applications will be invited to apply to Queen’s University Belfast.

Selection criteria

Applicants should demonstrate that they meet the following criteria:

* These criteria will be assessed at interview via a pre-interview exercise.

HDR UK reserves the right to reject applicants who do not meet the criteria at any stage. Regretfully, we can only provide feedback for candidates who reach interview.

Programme Structure

The four-year programme is divided in two. There is an initial Foundation Year followed by a three-year research project. The first year combines the best in university-based training with HDR UK-led national activities. And we support students to produce game-changing research plans and their projects are backed by substantial research funding.

Foundation year

3-5 day immersion events allow students to gain insight into the work of HDR UK, and our academic, clinical and industry partners. Courses may be residential (expenses provided) with up to a week away from their home university or online. Students undertake an intensive deep dive into an important area of health data science. Immersion topics include risk prediction, oncology, clinical trials, epidemiology and bioinformatics. Past immersion weeks have been hosted by the Universities of Birmingham, Manchester, Oxford and University College London and the European Bioinformatics Institute.

The immersion events encourage students to work together and stimulate new interactions:

• Axes of Prognosis
• The Different Facets of Data

Research areas

PhD research projects can be linked to The Institute’s:

• Research priorities
• Research hubs
• Partnerships

Team working

Students operate as a national cohort and work collaboratively with others, overcoming traditional institutional silos. Students are registered with a  partner university  but can draw on academic expertise from across the HDR UK network and are supported to formulate research activities that bring together experts from across the UK.

• You can contact us at [email protected]   or phone (+44 (0)770 847 8846). 
• For details of how we process applicants’ data see PhD Applicant Privacy Notice .

Students have access to graduate-level courses and research project rotation in their university to introduce them to different areas of health data science and enable them to develop a bespoke research project under the guidance of our expert university leads.

Regular workshops and short courses introduce students to the work of HDR UK experts across our hubs, themes and priority areas and to external organisations. Past contributors have included NHSX, IQVIA and AstraZeneca.

Immersion and workshop events allow students to better understand the wider health and social care landscape and accelerate their potential to become sector leaders. They also enable students to develop more ambitious PhD research projects by stimulating collaboration with external academics, industry-based organisations, or by using national data infrastructure.

Training is provided by academic, industry and NHS experts to promote personal and professional development in leadership capability, cross-sector collaborative skills and inter-disciplinary working. In particular, HDR UK is committed to working with public and patients to build increased trust in health data research as well as designing solutions focused on improving patient outcomes and experience. Students will develop communication and collaborative skills to help put them at the forefront of this mission.

At the end of the Foundation Year students design a bespoke three-year research project and a multi-disciplinary supervision team based on their training experiences.

Research proposals will be rigorously reviewed by expert academics and public-patient representatives to ensure they are of the highest standards in terms of ambition, scientific methodology and impact on patient outcomes.

The research will be carried out at their home university and could be linked to HDR UK  research priorities ,  research hubs  or  partnerships .

This includes short immersions plus  longer practical real-world projects with businesses and other organisations at the cutting edge of everything from medical devices, to life sciences, to vaccines. Students also learn about leadership theory and attend specially-convened seminars from senior figures in relevant areas of healthcare.

Networks and experience: Students will be actively supported in building networks and contacts in academia, the NHS and industry as well as taking internships and other opportunities to gain real-world experience.

Team working: Students operate as a national cohort, building strong relationships through joint activities and overcoming traditional institutional silos.

Workshops: Regular workshops and short courses introduce the work of HDR UK experts and to external organisations.

Immersion events: These allow students to better understand the wider health and social care landscape and accelerate students’ potential to become a sector leader. They also enable them to develop an ambitious PhD research project.

Researcher development: Training is provided by academic, industry and NHS experts to promote personal and professional development in cross-sector collaborative skills, communication and inter-disciplinary working.

“Our Leadership Programme will give PhD students the chance to develop the practical skills they need to bring people together to use health data science to deliver much-needed innovations and advances in health and care,”  Professor Peter Bannister

Our partners

Programme partners include NHS Digital, AstraZeneca, Moorfields Eye Hospital NHS Foundation Trust, and University Hospitals Birmingham.

More broadly it will work with winners of the NHSX AI Innovation Award , which funds and supports promising artificial intelligence technologies in health and care. There will also be opportunities with businesses on the DTI listed top 100 digital health innovators which are using big data for healthcare innovation.

Master’s Degree Scholarships

We offer 10 annual Master’s degree scholarships worth £10,000 for students with an interest in dementia or diabetes research.

Undergraduate Summer Internship in Health Data Research

Apply for a summer work placement in health data research at a UK research organisation, with an HDR UK-Wellcome Biomedical Vacation Scholarship

Join the HDR UK Alumni Network

HDR UK’s online Alumni Network brings together the amazing people who have been part of our training and education programmes.

Our host universities

- - - - Meet our PhD students

Our PhD students come from a wide range of backgrounds - discover who they are and what their experiences have been as part of the PhD programme

Meet the PhD Programme team

Our wider team consists of leading experts in disciplines including theoretical physics, computer science, mathematics and statistics, applied mathematics and biochemistry.

• Miguel Bernabeu – University of Edinburgh
• Ioanna Manolopoulou – University College London
• Niels Peek – University of Manchester
• Iain Styles – Queen’s University Belfast
• Paul Taylor – University College London
• Catalina Vallejos – University of Edinburgh
• Angela Wood – University of Cambridge
• David Wong – University of Manchester
• Tom Nichols – University of Oxford
• Magnus Rattray – University of Manchester

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Best Doctorates in Health Informatics: Top PhD Programs, Career Paths, and Salaries

Health informatics is an exciting public health field that is rapidly growing. To advance your career, you should consider pursuing one of the best PhDs in Health Informatics. These programs will prepare you for one of the many health informatics jobs available to PhD-holders.

A health informatics PhD takes about four to six years to complete, either online or in person. Continue reading to find our picks for 10 of the best PhDs in Health Informatics, as well as some of the top-paying jobs and PhD in Health Informatics salary information.

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What is a phd in health informatics.

A PhD in Health Informatics is a doctoral degree program that combines medical knowledge with computer and data science, engineering, and information science. This degree focuses on health information management and the collection, storage, and analysis of medical and patient data in the healthcare industry and clinical practice.

How to Get Into a Health Informatics PhD Program: Admission Requirements

The requirements to get into a health informatics PhD program include having a minimum of an undergraduate degree in a related field. Some PhD programs require a Master’s Degree in Health Informatics and at least three to five years of relevant work experience. Each program will require official transcripts from previous universities.

Additional requirements may include two to three letters of recommendation, GRE or GMAT test scores, a current resume, and a personal statement. English as a second language (ESL) students will need to provide proof of English proficiency in the form of Test of English as a Foreign Language (TOEFL) exam scores or the equivalent.

PhD in Health Information Admission Requirements

• Bachelor’s or Master’s Degree in Health Informatics or a related field
• Letters of recommendation
• Standardized test scores, such as GRE or GMAT
• Current resume showing relevant work experience
• Personal statement
• TOEFL exam or equivalent (for ESL students)

Health Informatics PhD Acceptance Rates: How Hard Is It to Get Into a PhD Program in Health Informatics?

It can be hard to get into a health informatics PhD program, but not harder than many other types of doctorate programs. Most schools have an acceptance rate of less than 40 percent. Doctoral students must be highly focused and qualified in their previous academic and work experience to be accepted into a PhD program.

How to Get Into the Best Universities

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Best PhDs in Health Informatics: In Brief

Best universities for health informatics phds: where to get a phd in health informatics.

You can find some of the best universities for health informatics across the United States in our list above. Depending on the school, you might have the option to choose between online or in-person learning. Below, we’ll take a close look at the best PhDs in Health Informatics.

Dakota State University was founded in 1881 as a teacher’s school. While educating future teachers remains an essential objective of the university, it has since shifted to focus on technology. The public university now enrolls over 3,000 undergraduate and graduate students annually. 

PhD in Information Systems

This flexible PhD in Information Systems program will allow students to learn comprehensive information systems with specialization options in healthcare, analytics, or security. Students will receive a balance of both theory and practice in key informatics concepts with the choice of completing this program full-time, part-time, online, or on campus. 

PhD in Information Systems Overview

• Program Length: 3 years
• Acceptance Rate: Not stated
• Tuition and Fees: $3,365/semester (in-state); $5,965/semester (out of state)
• PhD Funding Opportunities: General scholarships, graduate assistantships

Dakota State University Admission Requirements

• Bachelor’s degree or higher
• 3.0 minimum GPA
• GRE exam scores 
• Knowledge of business fundamentals and information systems

Indiana University was founded in 1820 as a public research university and the flagship campus of the Indiana University system. It began as State Seminary College before becoming Indiana College in 1829. Indiana University offers over 400 graduate degree and certificate programs to more than 8,500 graduate students. 

PhD in Informatics 

The PhD in Informatics program at Indiana University offers a specialization track in health. The program focuses on the standards, terminology, and electronic health data exchange of informatics. In addition, students will learn about mining clinical data, as well as developing and implementing health applications.

PhD in Informatics Overview

• Program Length: 4-5 years
• Acceptance Rate: 38.3%
• Tuition: $26,449/year
• PhD Funding Opportunities: Tuition remission, associate instructor and teaching assistant opportunities (full-time students only)

Indiana University Bloomington Admission Requirements

• GRE scores (optional)
• Official transcripts
• Three letters of recommendation
• Current resume

Liberty University is a private, nonprofit university that was founded in 1971. It is a private Evangelical university and one of the largest Christian universities in the world. Liberty University offers over 75 online and on-campus doctoral degree programs to more than 33,000 graduate students. 

Doctor of Business Administration in Healthcare Management

The Liberty University Doctorate in Business Administration in Healthcare Management offers a practical approach to healthcare informatics and trains students in healthcare management, quality healthcare systems, and human resource development. This 60-credit program can be completed entirely online within three years. 

Doctor of Business Administration in Healthcare Management Overview

• Acceptance Rate: 50%
• Tuition and Fees: $595/credit 
• PhD Funding Opportunities: Loans, federal aid, scholarships

Liberty University Admission Requirements

• Master's Degree in Business Administration or a related field
• Statement of purpose

University of Alabama at Birmingham (UAB) became an autonomous university in the University of Alabama System in 1969. UAB is a public research institution that is renowned for its graduate programs in health management and medicine. The university offers over 150 master’s and doctorate programs to more than 8,500 graduate students. 

PhD in Administration-Health Services

The University of Alabama at Birmingham’s PhD in Administration Health Service interdisciplinary program teaches students the fundamentals of health economics, health insurance, and the development of the US healthcare system. Students will also learn administrative theory, healthcare finance, and health policy.

PhD in Administration-Health Services Overview

• Program Length: 3-6 years
• Tuition and Fees: $465/credit (in-state); $1,098/credit (out of state)
• PhD Funding Opportunities: Primary instructor or teaching assistant positions, research assistantships, doctoral fellowships for minority students, and Blazer Graduate Fellowships

University of Alabama Birmingham Admission Requirements

• Master's or bachelor's degree with relevant work experience
• Updated resume
• GRE or GMAT exam scores
• Admissions interview

University of Florida (UF) is a public, land-grant research institution founded in 1906. The university is ranked 28th on the US News & World Report’s list of national universities . UF offers more than 700 doctoral degree programs to over 16,000 graduate students enrolled at its Gainesville campus. 

PhD in Medical Sciences, Biomedical Informatics

This 90-credit UF PhD program trains students in biomedical informatics, an interdisciplinary, health-centered field consisting of engineering, computing, biostatistics, medicine, and data science. Students of this program will learn cutting-edge technology, tools, and research methods to prepare them for health informatics careers in research and academia. 

PhD in Medical Sciences, Biomedical Informatics Overview

• Program Length: 5-6 years
• Acceptance Rate: 26%
• Tuition and Fees: $12,740/year (in-state); $30,134/year (out of state)
• PhD Funding Opportunities: Fellowships, McNair Doctoral Scholars Program, graduate research and teaching assistantships, tuition waivers, a yearly stipend of approximately $29,700

University of Florida Admission Requirements

• Master’s or bachelor’s degree in a relevant field
• 3.0 GPA (for bachelor’s degree holders)

University of Iowa (UI) is a large public research university founded in 1847. UI was the first coeducation medical school in the country and is the oldest university in Iowa. The university offers more than 100 graduate programs, 12 of which are among the top ten programs in the country. 

PhD in Health Informatics

The University of Iowa’s 72-credit PhD in Health Informatics degree program focuses on the processes used to improve healthcare-related data utilization. Students will explore topics such as storing medical information and important state and federal regulations regarding health care. 

PhD in Health Informatics Overview

• Acceptance Rate: 29%
• Tuition and Fees: $12,065/year (in-state); $31,012/year (out of state)
• PhD Funding Opportunities: Iowa Recruitment Fellowships, Post-Comprehensive Research Awards, Center for Advancement’s Student Impact Grant, T. Anne Cleary International Dissertation Research Fellowships

University of Iowa Admission Requirements

• Bachelor’s or master’s degree

University of Minnesota was founded in 1851 and is the oldest university in Minnesota. University of Minnesota began as a struggling college prep school before finding its footing and becoming the flagship campus of the University of Minnesota system. It is now the largest public university in Minnesota with a total enrollment of more than 51,000 students. 

PhD in Health Informatics 

This PhD in Health Informatics degree program offers multiple specialization options. The 70-credit Clinical Informatics track trains students in relevant clinical application methods, teaching them about health data, biostatistical methods, coding system analysis, and human-computer interactions. 

• Program Length: 4 years
• Acceptance Rate: 66%
• Tuition and Fees: $8,922/semester (in-state); $13,806/semester (out of state)
• PhD Funding Opportunities: Merit-based fellowships, graduate teaching, research assistantships

University of Minnesota Admission Requirements

• 3.5 minimum GPA recommended
• GRE exam scores

University of Texas Health Science Center at Houston was created in 1972 as part of the University of Texas System. UT Health Science Center at Houston is a part of the Texas Medical Center, which is the largest in the world of its kind. The university is considered Texas' source of health education and was the first to offer an advanced degree in health informatics.

PhD in Biomedical Informatics

University of Texas Health Science Center at Houston features a 93-credit, on-campus doctoral program that trains students in fundamental informatics concepts, theories, and practices that can be applied to all areas of health care. Students work in teams to conduct cutting-edge research and aim to solve real-world biomedical problems in the field. 

PhD in Biomedical Informatics Overview

• Program Length: 4-years
• Tuition and Fees: $4,944/semester (in-state); $11,808/semester (out of state)
• PhD Funding Opportunities: Full-ride scholarships based on merit, graduate teaching, research assistantships

University of Texas Admission Requirements

• Bachelor’s or master’s degree 
• Three letters of recommendation 
• Personal goals statement

University of Utah opened its doors in 1850 as University of Deseret. In 1892, the college changed its name to University of Utah. It remains the oldest institute of higher education in Utah. The university offers more than 200 graduate and doctoral degree programs to over 8,000 graduate students.

PhD in Biomedical Informatics 

University of Utah’s PhD in Biomedical Informatics program has a specialization track in Health Care and Clinical Informatics. This program works closely with the Nursing Informatics program to teach students how to support the implementation of evidence-based practices, as well as the foundational concepts and technology of electronic health records.

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• Program Length: 3-4 years
• Tuition and Fees: $4,139.44/credit (in-state); $7,384.96/credit (out of state)
• PhD Funding Opportunities: Fully funded tuition for all admitted students, including a yearly stipend of $29,710

University of Utah Admission Requirements

• Bachelor’s degree or higher 
• 3.3 minimum GPA

Founded as Milwaukee Normal School in 1885, University of Wisconsin - Milwaukee is the largest university in the Milwaukee metro area. Since changing its name to University of Wisconsin - Milwaukee (UWM) in 1956, it has become home to over 24,000 students and 4,700 graduate students.

PhD in Biomedical and Health Informatics

Students enrolled in UWM’s biomedical PhD program are trained in health care management processes and technology that support medical records, instrumentation, and information processing needs of consumers and clinics. Students of this program will have the necessary skills and expertise to become research leaders in the field. 

PhD in Biomedical and Health Informatics Overview

• Program Length: 3-5 years
• Tuition and Fees: $12,219/year (in-state); $25,650/year (out of state)
• PhD Funding Opportunities: McNair Fellowship, graduate teaching and research assistantships, Advanced Opportunity Program Fellowship, Distinguished Dissertation Fellowship, Distinguished Graduate Student Fellowship

University of Wisconsin - Milwaukee Admission Requirements

• Master’s Degree in Biomedical and Health Informatics or a related field ( exceptionally qualified candidates with a bachelor’s degree in a related field may be considered)

Can You Get a PhD in Health Informatics Online?

Yes, you can get a PhD in Health Informatics online. An online program allows you to take courses that fit into your personal work schedule, as many programs are intended for students who are already working in the health informatics field.

Best Online PhD Programs in Health Informatics

How long does it take to get a phd in health informatics.

It typically takes between three to five years of full-time study to get a PhD in Health Informatics. Usually, core courses are completed within the first two years and electives are completed in the third year. In the final year of your health information technology doctoral degree program, you will work on your dissertation, capstone project, or doctoral thesis. Some programs require a comprehensive exam in addition to the culminating project requirement.

Is a PhD in Health Informatics Hard?

Yes, a PhD in Health Informatics can be hard to obtain, with many hours spent studying and conducting research in challenging areas of the field. A health informatics program requires students to have knowledge in complicated disciplines like computer science, biostatistics, and medicine.

Additionally, a PhD requires more than just technical skills. You’ll also need to focus on important soft skills such as leadership, communication, and teamwork. Nonetheless, with hard work and dedication, getting a PhD in Health Informatics is more than possible to achieve.

How Much Does It Cost to Get a PhD in Health Informatics?

It costs $19,314 to get a PhD in Health Informatics, according to the National Center for Education Statistics. However, this value is an average of the tuition costs of all graduate degree-granting institutions. The total cost will vary on different factors, such as whether the university is public or private and whether you are a resident or non-resident.

How to Pay for a PhD in Health Informatics: PhD Funding Options

Most schools offer numerous PhD funding options that students can take advantage of to pay for a PhD in Health Informatics program. These options often include loans, scholarships, and fellowships. Most of these options are based on merit and need, so you should look into what options are offered by the school and how to apply for them.

Some schools also offer fully-funded PhD programs that cover the total cost of tuition and fees, as well as provide a yearly stipend. In these programs, students work in research or teaching assistantships in exchange.

Best Online Master’s Degrees

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What Is the Difference Between a Health Informatics Master’s Degree and PhD?

The difference between a health informatics master’s degree and a PhD is the curriculum and the overall length and level of study. A master’s degree is a graduate program that will help you obtain the relevant technical skills needed for a job in the health informatics field. These degrees typically take two years and go beyond the general topics taught in an undergraduate program.

While a master’s degree features more advanced studies than a bachelor’s degree, the PhD takes it a step further and focuses on specific learning tracks like data science, clinical informatics, and precision medicine informatics. PhDs take four to six years to complete and are the highest educational qualification you can receive in any field of study.

Master’s vs PhD in Health Informatics Job Outlook

Health informatics is a rapidly growing field. According to the US Bureau of Labor Statistics, medical and health services managers have an outlook of 32 percent job growth by 2030. This profession requires a master’s degree and many years of relevant experience, or a PhD, DHA, or equivalent.

On the other hand, records and health information specialists, a profession that only requires an associate or bachelor’s degree, are expected to see job growth of nine percent by 2030 , a rate that is much lower than that of health services managers.

Difference in Salary for Health Informatics Master’s vs PhD

The average salary for someone with a Master’s Degree in Health Informatics is approximately $65,000 per year, according to PayScale. In comparison, PhD holders earn an average annual salary of $119,000 per year . PhD candidates are more qualified by default and can work in high-paying senior managerial and research positions, or teach in higher education institutions.

Related Health Informatics Degrees

[query_class_embed] https://careerkarma.com/blog/best-health-informatics-associate-degrees/ https://careerkarma.com/blog/best-health-informatics-bachelors-degrees/ https://careerkarma.com/blog/health-informatics-masters-degrees/

Why You Should Get a PhD in Health Informatics

You should get a PhD in Health Informatics because you will gain in-depth, expert-level knowledge of the healthcare industry and the skills necessary to best support patient information storage. A PhD program will allow you to learn excellent research, technical, analytical, and theoretical skills and concepts that will prepare you for the career of your choice.

Reasons for Getting a PhD in Health Informatics

• Career opportunities. Health informatics is a growing field with plenty of career opportunities. As more jobs open in this field, more managers with the appropriate education are necessary. Those with a PhD are the most qualified candidates and will find an abundance of available positions to apply for.
• Interesting work. There are many interesting and exciting facets to a career in the health informatics field. An analytically-minded candidate can create databases, analyze patient data, and create applications to maintain data and ensure patient privacy.
• Higher earning potential. Having a PhD enables you to demand a high salary and great benefits. Because it is the highest qualification possible, PhD holders are able to negotiate higher salary compensation in comparison to those with bachelor’s or master’s degrees.
• Specialized education. A PhD allows you to focus on specific areas of health informatics that interest you most. This specialization experience can make you an expert on a particular subject and help you with your career after graduation.

Getting a PhD in Health Informatics: Health Informatics PhD Coursework

A PhD in Health Informatics program requires several core courses to earn your degree. Health informatics PhD coursework explores the fundamentals of informatics, as well as specialization or elective courses based on your interests. Below are a few of the most common courses you may see in a program’s health informatics curriculum.

Introduction to Health Informatics

In an introductory informatics course, students will learn fundamental informatics concepts with a more refined look at the relevant health information technology used in the field. The course explores the data types, use of data, and relevant modeling processes to store and process patient data.

Introduction to Biostatistics

An introduction to biostatistics class focuses on biological data and the statistical techniques used to sample and analyze data. Students work with hypothesis tests, simple linear regression, and categorical data analysis.

Database Systems

Database systems classes explain how to create and query databases. Students will learn how to use SQL, ER diagrams, and develop relational databases. They will also learn to program web applications using JDBC or PHP.

Human-Computer Interactions

Human-computer interactions courses teach students about UX design programs and how consumer behavior applies to user experience design. This course also covers the concepts and practices of informatics architecture.

Health Information Technology Policy

Health information technology policy focuses on key policy issues in the United States. Some courses may also cover a few international policies. They focus on the three major areas of consumer, clinical, and biomedical informatics.

Best Master’s Degrees

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How to Get a PhD in Health Informatics: Doctoral Program Requirements

Knowing exactly how to get a PhD in Health Informatics is essential before applying for a doctoral program. Many programs require a certain amount of credit hours, publication requirements, and a dissertation or capstone project. While each program varies slightly, you should be prepared to complete each of the following steps before you graduate.

All universities will require a certain amount of credit hours to be completed before graduation. These requirements can range from 60 to more than 100 credit hours for a PhD program. 

Some universities require a capstone project in place of a doctoral thesis. Students typically spend their final year of studies working on a capstone project. You will have to announce your project to the department and have it approved before you start working on it.

Many universities require PhD candidates to spend their final semesters working on a research dissertation or thesis. Your thesis will need to consist of original research with a full explanation of the conclusions you've reached during your project. 

Once you have completed your thesis, you will have to attend a meeting with your advisor and other PhD department faculty. During this meeting, you will orally present your research and findings, and you will be asked questions about your thesis. You must answer the questions in a way that convinces the faculty that you have successfully completed doctorate-level work. 

During your first and second years of the PhD program, you will have to take and pass comprehensive exams. These exams are often quite challenging and prove that you have successfully retained and mastered the information learned in your first few years of study. 

Potential Careers With a Health Informatics Degree

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PhD in Health Informatics Salary and Job Outlook

Professionals with a PhD in Health Informatics can earn six-figure salaries per year. Health informatics is a growing field, with most jobs featuring an above-average job growth outlook within the next decade.

What Can You Do With a PhD in Health Informatics?

With a PhD in Health Informatics, you can work in the public or private health care system, keeping clinics and hospitals in line with federal regulations. Many career options requiring a PhD in Health Informatics include leadership or educator roles.

Best Jobs with a PhD in Health Informatics

• Health IT Project Manager
• Nursing Informatics Director
• Health Services Director
• Postsecondary Education Administrator
• Clinical Analyst

What Is the Average Salary for a PhD in Health Informatics?

The average salary for someone with a PhD in Health Informatics is $119,000 per year . Health informatics can extend to nursing informatics director roles, which require a Doctor of Nursing Practice degree. However, these professionals perform many of the same tasks as those with a PhD.

Highest-Paying Health Informatics Jobs for PhD Grads

Best health informatics jobs with a doctorate.

The best health informatics jobs for doctoral degree holders include management and director positions. Most of these positions require a postgraduate degree and several years of relevant work experience in the informatics field.

Health IT project managers are in charge of installing and maintaining hardware, software, and all computer-related activities and goals for a health organization. In addition, they analyze an organization’s technological needs and work to ensure project objectives and goals are completed by required deadlines.

• Salary with a Health InformaticsPhD: $159,010
• Job Outlook: 11% job growth from 2020 to 2030
• Number of Jobs: 482,000
• Highest-Paying States: New York, California, and New Jersey

A nurse informatics director is a nurse practitioner responsible for being a bridge between the clinical side and IT department of a health organization. These professionals facilitate communication between vendors, faculty, and IT department staff. They also evaluate new IT applications and train staff on new technology.

• Salary with a Doctorate Nurse Practitioner- Nurse Executive: $123,780
• Job Outlook: 45% job growth from 2020 to 2030
• Number of Jobs: 271,900
• Highest-Paying States: California, New Jersey, New York

A postsecondary teacher develops a teaching plan for the relevant informatics courses they teach. They may teach multiple lessons in their department each semester. They instruct university students on course topics, stay informed about subject changes, and assess student progress.

• Salary with a Health Informatics PhD: $102,720
• Job Outlook: 12% job growth from 2020 to 2030
• Number of Jobs: 242,700
• Highest-Paying States: Washington, Mississippi, and Connecticut

A health services manager is directly responsible for developing and overseeing important clinical department tasks. These tasks include hiring, training, evaluating, and supervising all clinical employees. They must also work with financial department staff to develop relevant program budgets.

• Salary with a Health Informatics PhD: $101,340
• Job Outlook: 32% job growth from 2020 to 2030
• Number of Jobs: 429,800
• Highest-Paying States: New York, Washington DC, and Massachusetts

A clinical analyst is responsible for evaluating data and maintaining a healthcare facility’s clinical information system. It is a clinical analyst’s responsibility to create and maintain all database systems used by the facility, interpret and analyze data, and come up with solutions to technical problems. 

• Salary with a Health Informatics PhD: $70,601
• Number of Jobs: 100,500
• Highest-Paying States: Washington DC, Massachusetts, and California

Is a PhD in Health Informatics Worth It?

Yes, a PhD in Health Informatics is worth it. With a rapid growth rate, there is a need for well-educated employees in the field. Doctoral degree holders have the option of choosing between working on the analytical or technical sides to meet their interests.

A doctoral student in health informatics should focus on finding a program that matches their desired learning track. Several graduate schools offer focused informatics tracks that will allow you to use the informatics practices that interest you most.

Additional Reading About Health Informatics

[query_class_embed] https://careerkarma.com/blog/health-informatics/ https://careerkarma.com/blog/health-informatics-careers/ https://careerkarma.com/blog/masters-in-health-informatics-scholarships/

PhD in Health Informatics FAQ

Yes, you can work from home with a degree in health informatics. However, many of the positions that are exclusively available to PhD-holders require you to work in person.

Yes, health informatics is considered a STEM major. With an educational focus on the health care field and data analysis, health informatics falls into both categories of science and technology.

No, you don’t need to know how to code for a health informatics degree. However, it may be beneficial to have some coding knowledge if you are tasked with building a new database.

No, you typically cannot work as a health informatics professional without a degree. It is a technical field that requires a foundational understanding of the relevant systems and protocols. Therefore, you must have at least a bachelor’s degree to begin your professional journey and gain experience in the field.

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NOV 2: Health Data Science Distinguished Speaker Series: Dr. Rumi Chunara, NYU

"Machine Learning in Population Health: Challenges & Opportunities" Nov 2, 2023 | 12-1PM.   Hiebert Lounge & Zoom. Register here. Dr. Read more

NOV 29: Research on Tap: Health Data Science

Nov 29, 2023 | 4-6PM.  Kilachand Center (610 Comm Ave), Room 101. Register here. The goals of this Research on Read more

DEC 11: Workshop on Introduction to Machine Learning

Instructors: W. Evan Johnson and Vijaya B. Kolachalama. Dec 11, 2023 | 11:30AM - 2:30PM.  Hiebert Lounge. Lunch provided.  Registration is now closed. Read more

JAN 24: Health Data Science Distinguished Speaker Series: Dr. Suresh Venkatasubramanian, Brown University

"The Moral Salience of the Algorithmic Lens" Jan 24, 2024 | 12-1PM.  Hiebert Lounge & Zoom. Register now:   Abstract:  Read more

FEB 15: Health Data Science Distinguished Speaker Series: Dr. Tamara Broderick, MIT

"Toward a Taxonomy of Trust in Data Science Methods" Feb 15, 2024 | 11:30AM-12:30PM. Hybrid Event (BUMC & Zoom). In-person:  Read more

Health Data

This course provides an introduction to data sources commonly used for health care research and analysis. Topics will include publicly available data sources, identifying strengths and weaknesses of data sources, and data management. By the end of the course students will be able to identify a large number of available data sources for research and analysis, understand their strengths and weaknesses, assess whether a particular data source is appropriate for a given project, and manage and work with health data.

Weill Cornell Medicine Graduate School of Medical Sciences 1300 York Ave. Box 65 New York, NY 10065 Phone: (212) 746-6565 Fax: (212) 746-8906

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• Accessibility
• EPSRC Centre for Doctoral Training in Health Data Science

EPSRC Centre for Doctoral Training in Healthcare Data Science

Course structure

Research & ethics, student experiences, follow us @hdscdt.

Insights derived from the analysis of large, complex data sets will make significant contributions to the prevention and treatment of disease. The aim of this doctoral training  programme  in Healthcare Data Science is to offer systematic training in statistics, machine learning, and data management. Core to the entire  programme  is to combine this technical training with a foundation in ethics.  

Ethics plays a central role in health data science, and our approach to doctoral training reflects this. Ethics and research responsibility is a vertical theme running through the four years of the  programme . Each of the first two terms begins with a week of training in ethics, responsible research and innovation, and collaborative working. In the first term, this training addresses ethical issues in data science and big data in general. In the second, it focuses upon specific ethics and governance issues in health data science and healthcare delivery.  

This EPSRC Centre for Doctoral Training in Healthcare Data Science  is located in  the Big Data Institute/Oxford Population Health Building at the University of Oxford.

ENTRY REQUIREMENTS

A data science subject degree including Mathematics, Statistics, Engineering Science, Computer Science or a related field with substantial mathematical background. Applicants are recommended to have completed an MSc in one of the above subjects.  

How to apply

We're delighted that this programme has been renewed as the EPSRC CDT in Healthcare Data Science for another five cohorts starting from October 2024. Please see the admissions page on the University website for information about entry this autumn.

This course is taking part in a continuing pilot programme to improve the assessment procedure for graduate applications, to ensure that all candidates are evaluated fairly. For this course, the socio-economic data you provide in the application form will be used to contextualise the shortlisting and decision-making processes where it has been provided. Please carefully read the instructions concerning submission of your CV/résumé, statement of purpose, transcript and letters of support from referees in the  How to apply  section of this page as well as the  full details about this pilot .

It is important that you follow these new steps for your application to be considered.  Please use the standardised CV template provided and do not upload your own personalised version as these will not be reviewed by the Directorate.

Please ignore the section that states referees should anonymise their references, this applied to other courses on the pilot scheme but not ours.

We suggest considering Reuben College  or Kellogg College as the CDT has forged partnerships with these colleges. You are of course free to select any college on your application form but the CDT encourages you to consider one of these two listed colleges.

RESEARCH ENVIRONMENT

The Centre is hosted within the Big Data Institute (BDI)/Oxford Population Health (OxPop) Building, a purpose- built building  at the heart of the University of Oxford's biomedical campus. The Big Data Institute is an analytical hub for multi-disciplinary working at Oxford, connecting world-leading expertise in statistics, computer science, and engineering to data-driven research in clinical medicine and population health. It is also home to the  Ethox  Centre , a world-leading  centre  for clinical and research ethics, and the   Oxford Centre for Ethics and Humanities . 

The building hosts the clinical informatics and big data activity of the National Institute for Health and Care Research (NIHR) Oxford Biomedical Research Centre (BRC), a substantial  programme  of translational research, delivered by the University in partnership with Oxford University Hospitals (OUH) NHS Foundation Trust .  CDT students will have the opportunity to contribute to the work at the BRC, to access the expertise of the team, and to become involved in multi- centre  research collaborations.  

The BDI/OxPop Building is also home to UK Biobank , a major national and international resource for health research. The Biobank team are leading the development of tools for the acquisition, processing, analysis, and re-use of data from clinical and online assessments, imaging, sensors, genotyping, and national datasets (including hospital episodes, death, and primary care) for a cohort of 500,000 participants. CDT students will have the opportunity to access the expertise of the team, and to become involved in Biobank-based research.  

Connecting healthcare companies with physicians.

Precision Healthcare Data’s (PhD) online portal and innovative user interface connects critical healthcare data and business intelligence for over 5.2 million health care professionals across 700 specialties with over 860,000 emails.

We make connections.

Our solutions connect your sales and marketing teams enabling use cases including targeting, sales resource planning, market prioritization, local area marketing, physician profiling, trend analysis, market research and more.

Our data connects you with healthcare professionals.

Our physician names, addresses and emails are connected to their procedure and prescription history, which are further connected to the physical locations where they practice.

Our portal connects you to the data.

Build custom physician audiences based on their specialties, prescribing habits, procedures, diagnostic testing capabilities, geographic markets and more.

Focus your sales team

Identify pockets of opportunity within your markets, enhance your crm for gap analysis, source your market research with the right audiences, act on trends, build meaningful segmentation, optimize your sales resources, profile markets and physicians to differentiate your messaging, how do i get started.

Step one is a meeting with a PhD consultant to help us understand your key audiences and use cases. Once we understand your desired outcomes, we will recommend a set of databases — you only pay for the data you need. Getting started is easy, in most cases it’s a 1-hour tailored training session.

What kind of support can I expect?

Our portal is self-serve, and it really is easy to use, but that doesn’t mean you’re on your own. We encourage communication. We believe our data has legs across the enterprise. For example, think about CRM integrations and the power in measuring YoY changes in acquisition, retention, reactivation and loyalty. Isolate where you’re winning and losing. Instead of running ad-hoc campaigns, let us help you run more targeted approaches to win more and lose less.

How much does it cost?

Our pricing is modular. You pay an annual license fee for only the data you need. One-year or multi-year commitments and no sneaky auto renewals. Our consulting is included.

Is there an additional cost to export data to my CRM?

No. Exporting the data is included in your annual license. As long as the data is being used within the walls of your enterprise, you may export to any internal environments. You may also share our data with key partners such as distributors and market research partners as long as the data is being used solely on your behalf.

Let's talk.

We would love to talk with you — we want to learn more about your audience segments, your data, your desired outcomes. Then we can make suggestions on how to drive efficiencies across your organization. And we’re happy to give you a live demonstration of our data and solutions.

Precision Healthcare Data is changing the way healthcare companies connect with physicians.

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The Role of Data in Public Health Equity and Innovation Conference

At the Yale School of Public Health, we believe that the future of public health will be defined by four pillars: inclusivity, innovation and entrepreneurship, communication, and data-driven leadership. It is through this commitment to data-driven leadership that we will convene a global, diverse and interdisciplinary group of leaders from academia, government, healthcare, and private industry.

Over the course of this two-day event, we will engage experts in three thematic areas central to the conference:

1) The depiction of social determinants of health in data

2) Community-based models for data

3) The effect of artificial intelligence on health data equity.

The program for Monday, April 8 will be a full day comprised of a series of keynote speeches, moderated panel discussions on each thematic area, and a fireside chat. On April 9th, we will be hosting a half-day of closed-door roundtable discussion. We hope the roundtables will lead to opportunities for intersectoral collaboration across research and practice.

PLEASE NOTE: This event is open to members of the Yale community and free to attend but space is limited. Registration is required.

AGENDA - DAY 1

8:30-9:00 – Registration, Breakfast, Welcome Remarks

9:00-9:50 – Keynote speech Professor Bola Owolabi – MRCGP, MFPH Hon, FRSPH, Director of the National Healthcare Inequalities Improvement Programme, National Health Service England

9:50-10:55 – Comparative Themes on Data, Health Policy and Health Equity in the U.S. and UK Moderator:

Kaakpema “KP” Yelpaala, MPH – Lecturer and Senior Fellow in Public Health (Health Policy); Faculty Director, InnovateHealth Yale

Discussants:

• Professor Bola Owolabi, MRCGP, MFPH Hon, FRSPH – Director of the National Healthcare Inequalities Improvement Programme, National Health Service England
• Marcella Nunez-Smith, MD, MHS

10:45-11:00 – Coffee Break

11:00-12:10 – The depiction of social determinants of health (SDOH) in data

Dr. Bhramar Mukherjee – John D. Kalbfleisch Distinguished University Professor, Siobán D. Harlow Collegiate Professor of Public Health, and Chair of Biostatistics; Professor of Epidemiology and Global Public Health, UM School of Public Health

• Monica Bharel, MD, MPH – Clinical Lead Public Sector Health at Google
• Stephanie Pugliese, MPH – Director, Office of eHealth Innovation for the State of Colorado
• Ines Maria Vigil, MD, MPH, MBA – SVP Services & Transformation at Clarify Health

12:10-1:10 – Lunch

1:10-2:20 – Community-based models for data

Kim Gallon, PhD, MS, MLIS – Associate Professor of Africana Studies, Brown University

• Mark Abraham, MPH, Data Haven
• Oliver J. Bear Don’t Walk, IV, PhD, Aspaálooke - Postdoctoral Scholar, The University of Washington
• Michelle Wilson, Chief, Health Equity Institue, RIDOH

2:20-3:10 – Keynote speech

Professor Munmun De Choudhury, PhD, Associate Professor at the School of Interactive Computing in Georgia Institute of Technology

3:10-3:40 – Coffee Break (and solar eclipse viewing)

3:40-4:50 – The effect of artificial intelligence on health data equity

Chris Gibbons, MD, MPH – Founder & CEO of The Greystone Group

• Leying Guan, PhD – Assistant Professor of Biostatistics, Yale University
• Andrew Taylor, MD, MHS – Associate Professor of Biomedical Informatics and Data Science, Emergency Medicine, and Biostatistics, and Founder and Director of Yale Interdisciplinary AI & Medicine Lab, Yale University
• Asif Dhar, MD, MBA, – Vice Chair US Life Sciences & Health Care (LSHC) Industry Leader, Deloitte

4:50-5:00 –Speaker reception

AGENDA - DAY 2

8:30-12:30 - Closed-door roundtable discussions. Invite only.

National Health Service England

• Kaakpema Yelpaala Lecturer and Senior Fellow in Public Health (Health Policy); Faculty Director, InnovateHealth Yale
• Marcella Nunez-Smith, MD, MHS Associate Dean for Health Equity Research and C.N.H. Long Professor of Internal Medicine (General Medicine), of Epidemiology (Chronic Disease) and of Public Health (Social And Behavioral Sciences) & Professor of Internal Medicine (General Medicine); Affiliated Faculty, Yale Institute for Global Health; Founding Director, Equity Research and Innovation Center (ERIC), Yale School of Medicine; Director, Center for Research Engagement (CRE); Director, Center for Community Engagement and Health Equity; Deputy Director for Health Equity Research and Workforce Development, Yale Center for Clinical Investigation (YCCI); Director, Pozen-Commonwealth Fund Fellowship in Health Equity Leadership

UM School of Public Health

State of Colorado

Clarify Health

Brown University

Washington University

Georgia Institute of Technology

The Greystone Group

• Leying Guan Assistant Professor of Biostatistics (Biostatistics)
• Andrew Taylor, MD, MHS Associate Professor of Emergency Medicine and of Bioinformatics & Data Science; Director of Artificial Intelligence and Data Science, Emergency Medicine

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• Yale School of Public Health

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Data equity conference brings leaders together to reduce health disparities

A fireside chat at the conference.

In one of the fireside chats at The Role of Data in Public Health Equality and Innovation Conference April 8-9, Kaakpema "KP" Yelpaala (left), MPH ’06 (global health), senior fellow in public health (health policy) at YSPH and faculty director of InnovateHealth Yale (IHY), will talk to Bola Owolabi (center), director of the National Healthcare Inequalities Improvement Programme at the National Health Service (NHS) England; and Dr. Marcella Nunez-Smith, MD, MHS ’06, the inaugural associate dean for health equity research at the Yale School of Medicine (YSM), founding director of Yale’s Equity Research and Innovation Center (ERIC), and director of Yale’s Center for Community Engagement and Health Equity.

Advances in technology and the adoption of electronic medical records have generated an enormous amount of data about our health, providing researchers and practitioners with more insights into human illness and disease than they ever had before.

As public health scientists gather and probe these data and policymakers rely on them in making important decisions, it is critical that the information being generated and analyzed accurately reflect all individuals to reduce health disparities and create more equitable health systems.

Ensuring data equity is especially important given the increasing use of artificial intelligence (AI) in science and public health. AI is a powerful double-edged sword with the potential to both advance knowledge at lightening speeds and worsen existing disparities if not managed properly.

It is in this context that a global and diverse group of leaders from academia, government, health care, and private industry will gather at Yale on April 8-9 for a conference focused on The Role of Data in Public Health Equity and Innovation . The conference is organized by the Yale School of Public Health (YSPH), with support from the Whitney and Betty Macmillan Center for International and Area Studies.

Our hope is that this event is just the beginning of a longer trajectory of research and work with partners. We also hope to produce peer-reviewed papers from the roundtable discussions. Kaakpema "KP" Yelpaala

The event is structured to go beyond knowledge-sharing and discussions of central themes surrounding data equity. Attendees will also be encouraged to work together to identify innovative approaches and potential solutions to the problem. The April 8 discussions are open to the Yale community; the April 9 meetings will be closed-door sessions.

“Through this conference, we are focusing on three thematic areas: 1) the depiction of social determinants of health in data; 2) community-based models for data; and 3) the effect of artificial intelligence on health data equity. We will also convene round table discussions in each thematic area to start to chart a collaboration-oriented path forward on the themes discussed,” said conference organizer Kaakpema “KP” Yelpaala , MPH ’06 (global health), senior fellow in public health (health policy) at YSPH and faculty director of InnovateHealth Yale (IHY).

“Our hope is that this event is just the beginning of a longer trajectory of research and work with partners. We also hope to produce peer-reviewed papers from the roundtable discussions.”

There will be two keynote addresses. One will be delivered by Bola Owolabi , director of the National Healthcare Inequalities Improvement Programme at the National Health Service (NHS) England. She will discuss the NHS England’s health equity strategy and the role of data in supporting national and local priorities.

A second keynote address will be given by Munmun De Choudry , associate professor at the School of Interactive Computing at the Georgia Institute of Technology, where she directs the Social Dynamics and Well-Being Laboratory. Her research lies at the intersection of computer science and social sciences, focusing on leveraging large-scale data analytics and machine learning to understand human behavior and mental health dynamics in online environments. She is renowned for her groundbreaking contributions to the fields of computational social science, human-computer interaction, and digital mental health, and will be discussing themes related to AI and health for the event.

More information about conference discussion panels and speakers can be found on the conference’s web page .

YSPH Dean Megan L. Ranney, MD , has identified data-driven leadership as one of the four pillars of the future of public health, along with inclusivity, innovation and entrepreneurship, and communication. Data equity – the process of ensuring that data is representative, accessible, and contextualized for all people – is an integral part of that mission.

“One cannot close health disparities without thoughtful engagement on gathering and analyzing data over time and how we measure differences between groups,” Yelpaala said. “It is for this reason that I deeply believe in Dean Ranney’s commitment to the role of data in public health leadership. From a health equity perspective, we have to consider how our policies and solutions are closing disparity gaps, neutral in their impact, or potentially deepening health inequities for various populations.”

Yelpaala is particularly concerned about the rising use of artificial intelligence in science and public health. He fears that existing health inequities may be exacerbated if AI algorithms have internal biases or if they are applied to non-representative datasets.

“All human beings have different biases, and we produce AI-driven solutions,” he explained. “In my view, there is a risk of replacing one form algorithmic bias with another if we are not clear about the deeper definitions and concepts of bias, fairness, equity, and ethics that are being used. I am happy to see the recent guidance on AI in health from the World Health Organization (WHO), but we still have much work to do.” He added that these concepts vary from group to group and country to country, so it is not a straightforward issue for global alignment, even with guidance from the WHO.

Equitable data comes in many forms. The World Economic Forum recently identified four classes of data equity:

• Representation equity, which seeks to enhance the visibility of historically marginalized groups within datasets while also accounting for data relevancy for the target populations.
• Feature equity, which seeks to ensure the accurate portrayal of individuals, groups, and communities represented by data, necessitating the inclusion of attributes such as race, gender, location, and income alongside other data.
• Access equity, which focuses on the equitable accessibility of data and tools across varying levels of expertise, with an emphasis on addressing transparency and visibility issues related to model construction and data sources.
• Outcome equity, which pertains to impartiality and fairness in results. Beyond developing unbiased models, it entails maintaining vigilance over unintended consequences that impact individuals or groups.

As part of the April 8 program, Yelpaala also will conduct a fireside chat, “Comparative Themes on Data, Health Policy and Health Equity in the U.S. and UK,” with two internationally renowned public health experts: Owolabi and Dr. Marcella Nunez-Smith, MD , MHS ’06, the inaugural associate dean for health equity research at the Yale School of Medicine (YSM), founding director of Yale’s Equity Research and Innovation Center (ERIC), and director of Yale’s Center for Community Engagement and Health Equity . She also served as a senior advisor to the White House COVID-19 Response and chair of the Presidential COVID-19 Health Equity Task Force at the Department of Health and Human Services.

Owolabi will share how NHS England has approached health equity issues through its Core20PLUS5 model. She will also discuss how the health care inequalities improvement program approaches data as a way to not only shape health equity strategies, but also track progress. In addition to her other responsibilities, Nunez-Smith is Yale’s C.H. Long Professor of Internal Medicine, as well as a professor of epidemiology (chronic disease), of public health (social and behavioral sciences), and of management. She has done extensive research on promoting health and health care equity for structurally marginalized populations. Her work emphasizes the importance of community engagement, supporting health care workforce diversity, and developing patient-reported measurements of health care quality. She will discuss health equity in the very challenging, highly complex, and sometimes deeply fragmented U.S. health system.

Yelpaala said he is “very enthusiastic” about bringing two international leaders in health equity together to share their insights and perspectives, and the other panels and keynote address during the conference.

“I am particularly keen for the insights that will build from their exchange of ideas,” he said. “Every health system has strengths and areas of challenge. I am looking forward to Marcella and Bola engaging on the similarities and differences between their contexts, including policy opportunities, data gaps, and how they see the future of closing health disparities in each country.”

• Diversity and Inclusion

Featured in this article

• Kaakpema Yelpaala Lecturer and Senior Fellow in Public Health (Health Policy); Faculty Director, InnovateHealth Yale
• Marcella Nunez-Smith, MD, MHS Associate Dean for Health Equity Research and C.N.H. Long Professor of Internal Medicine (General Medicine), of Epidemiology (Chronic Disease) and of Public Health (Social And Behavioral Sciences) & Professor of Internal Medicine (General Medicine); Affiliated Faculty, Yale Institute for Global Health; Founding Director, Equity Research and Innovation Center (ERIC), Yale School of Medicine; Director, Center for Research Engagement (CRE); Director, Center for Community Engagement and Health Equity; Deputy Director for Health Equity Research and Workforce Development, Yale Center for Clinical Investigation (YCCI); Director, Pozen-Commonwealth Fund Fellowship in Health Equity Leadership
• Megan L. Ranney, MD, MPH Dean of Yale School of Public Health and C.-E. A. Winslow Professor of Public Health (Health Policy) and Professor of Emergency Medicine

U.S. News Releases 2024 Best Graduate Programs Rankings

Find the top-ranked graduate schools in business, education, law, nursing and other fields.

U.S. News Ranks Best Graduate Schools

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To help prospective graduate students find a school that fits their needs, U.S. News released the 2024 rankings for multiple graduate fields.

Depending on the job or field, earning a graduate degree may lead to higher earnings, career advancement and specialized skill development.

But with several types of degrees and hundreds of graduate schools, it can be difficult to narrow down the options. To help prospective graduate students find a school that fits their needs, U.S. News released its 2024 Best Graduate Schools rankings today. They evaluate business, education, fine arts, health, law, library studies, nursing, public affairs, science, and social sciences and humanities graduate programs. Medical school and engineering rankings are not being released at this time.

A notable methodology change includes a new salary indicator based on profession in the business rankings.

Additionally, for the first time in four years, there are new rankings for a blend of doctoral and master's programs in audiology, occupational therapy, physical therapy, pharmacy, nurse midwifery and speech-language pathology. Graduate programs in nurse anesthesia and social work are also ranked for the first time since 2016 and 2022, respectively. Those and other specialty rankings are based on reputation ratings from scholars at other surveyed schools.

Read each program's specific methodology for the most detailed explanations of all the changes. The rankings are one source of information among many that prospective college students can use to inform their college decision. Below is a summary of the top-ranked schools in four major graduate program areas:

Best Law Schools

Best business schools, best nursing schools, best education schools.

Among the top 10 law schools . Yale Law School in Connecticut and California-based  Stanford Law School shared the top spot again. The  University of Chicago Law School in Illinois maintained its No. 3 rank, followed by a four-way tie at No. 4: Duke University School of Law in North Carolina, Harvard Law School in Massachusetts, the University of Pennsylvania Carey Law School and the University of Virginia School of Law .

Columbia Law School in New York ranked No. 8 again, while there was a three-way tie for No. 9: New York University School of Law , Northwestern University's Pritzker School of Law in Illinois and the University of Michigan—Ann Arbor Law School .

Looking beyond the top 10, multiple law schools moved up in the rankings. William & Mary Law School in Virginia, for instance, jumped nine spots from a tie at No. 45 to a five-way tie at No. 36.

U.S. News also ranked 13 law specialties: business/corporate, clinical training, constitutional, contracts/commercial, criminal, dispute resolution, environmental, health care, intellectual property, international, legal writing, tax and trial advocacy. (You can filter by specialty on the  main ranking page .)

Meanwhile, in the  part-time law school rankings – which consists of law schools with at least 20 part-time students enrolled in fall 2022 and fall 2023 – the top three stayed the same. The  Georgetown University Law Center in Washington, D.C., is once again at the top while D.C.-based  George Washington University Law School , now No. 3, switched places with the  Fordham University School of Law in New York City, which claimed second place.

Previously ranked at No. 3 and No. 6 respectively, the University of Pennsylvania's Wharton School and Stanford Graduate School of Business took the top spot in this year's full-time MBA program rankings . Northwestern's Kellogg School of Management and the University of Chicago's Booth School of Business moved down from their previous places in the top two to tie at No. 3.

While the top 10 mostly consists of the same schools as last year, both the Haas School of Business at the University of California, Berkeley and the University of Virginia's Darden School of Business joined those ranks this year. UC Berkeley rose from a three-way tie at No. 11 to a three-way tie at No. 7, while UVA moved up four spots from No. 14 to a tie at No. 10.

Farther down the full-time MBA rankings, there were some big changes. For example, Pitt's Joseph M. Katz Graduate School of Business soared 39 spots from a tie at No. 86 to a tie at No. 47.

Meanwhile, the very top of the part-time MBA rankings looks similar to last year, with the same schools in the top 5: UChicago, UC Berkeley, Northwestern, NYU's Leonard N. Stern School of Business and the Anderson School of Management at the University of California—Los Angeles. But UChicago took the No. 1 spot from UC Berkeley this year.

Moving up from No. 2, Johns Hopkins University School of Nursing in Maryland tied with Emory University's Nell Hodgson Woodruff School of Nursing in Georgia to claim the top spot in this year's nursing master's program rankings. Duke University School of Nursing in North Carolina climbed up by one to claim the third spot.

Johns Hopkins ranked No. 1, as it did last year, in the Doctor of Nursing Practice program rankings. George Mason University School of Nursing in Virginia – which reported more graduates and resources per faculty – soared from a four-way tie at No. 39 to take the No. 2 spot. Duke tied with the University of Washington School of Nursing to round out the top three.

Duke also ranked No. 1 in all of the ranked nursing master's nursing practice specialties, including administration, family, both acute and primary care adult gerontology, and mental health.

Once again, Teachers College, Columbia University in New York was No. 1 in the graduate education schools rankings. This year, however, it tied with the University of Wisconsin—Madison School of Education , which climbed two spots.

The University of Michigan—Ann Arbor's School of Education dropped from the top position to tie with the UCLA School of Education and Information Studies at No. 3. UCLA was previously tied at No. 7.

U.S. News also ranks nine education specialties, with the College of Education at Michigan State University claiming the top spot in the following categories: curriculum and instruction, educational administration, elementary teacher education, higher education administration and secondary teacher education.

Searching for a grad school of education? Access our  complete rankings  of Best Graduate Schools.

Grad Degree Jobs With $100K+ Salaries

Tags: students , graduate schools , medical school , business school , law school , education graduate school , engineering graduate school , MBAs , nursing programs

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Master of Science in Health Data Science

Leverage your skills in statistics, computer science & software engineering and begin your career in the booming field of health data science

The Master of Science (SM) in Health Data Science provides students with the rigorous quantitative training and essential computing skills needed to manage and analyze health science data in order to address important questions in public health, medicine, and basic biology.

Offered by the Department of Biostatistics, this new 60-credit program is designed to provide participants with the knowledge base and targeted skills required for rigorous work in health related data science. Students will learn to:

• Critically explore, analyze and interpret data
• Appropriately apply statistical inference to make scientific conclusions from data
• Understand and employ linear models, regression and matrix algebra
• Apply methods for high-dimensional data
• Implement machine learning algorithms
• Develop and write software
• Communicate and disseminate results via reproducible reports
• Be proficient with high performance scientific computing
• Effectively wrangle data
• Perform data visualization
• Design experiments

The SM in Health Data Science is designed to be a terminal professional degree, giving students essential skills for the job market. At the same time, it provides a strong foundation for students interested in continuing in a PhD in Biostatistics or other quantitative or computational science with an emphasis in data science.

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UB schools among the best in U.S. News & World Report’s Best Graduate Schools rankings

Photo: Douglas Levere

By David J. Hill

Release Date: April 9, 2024

BUFFALO, N.Y. – Several schools within the University at Buffalo, New York’s flagship, are ranked among the top nationwide in U.S. News & World Report’s Best Graduate Schools rankings , released this morning.

The School of Pharmacy and Pharmaceutical Sciences is among the top 20 in the country, coming in at No. 19 overall and 18th among public universities.

“This achievement is a testament to our relentless pursuit of groundbreaking research, transformative discoveries, and unwavering commitment to the success of our students,” said Gary Pollack, PhD, dean of the School of Pharmacy and Pharmaceutical Sciences. “Our top 20 ranking reaffirms our steadfast commitment to cultivating the next generation of pharmacy and pharmaceutical science leaders who will push the boundaries of scientific inquiry, drive innovation in patient care, and elevate the standards of pharmaceutical research on a global scale.”

The School of Social Work is once again in the top 25, coming in at 24th nationally and No. 13 among public universities.

The School of Nursing’s Doctor of Nursing Practice (DNP) program moved up 11 spots to 34th in the country and No. 24 among public universities. In addition, the nursing anesthesia program was ranked 22nd.

“We are immensely proud to rank among the best DNP programs in the United States,” says School of Nursing Dean Annette Wysocki, PhD. “Our commitment to exceptional nursing education cultivates discipline of the mind to educate highly discerning nurse practitioners, who are indispensable in addressing the nation’s critical shortage of primary care providers. Quality nursing education remains paramount in safeguarding the health and wellness of our community.”

UB’s Graduate School of Education moved up four spots to No. 54 in Best Education Schools. Among public universities, the Graduate School of Education ranks 42nd. “Our steady climb in the rankings over the years is a testament to the hard work and high-quality research of GSE faculty,” says dean Suzanne Rosenblith, PhD.

The School of Public Health and Health Professions moved up four spots, to No. 46 nationally and No. 29 among public universities. Its programs in occupational therapy (41) and physical therapy (74) were also ranked, as was biostatistics (22).

Meanwhile, the School of Law moved up 17 places to No. 108 among Best Law Schools nationwide and 56th among public universities.

The School of Management’s MBA program came in at No. 74 in Best Business Schools and 38th among public universities, making it the highest rated business school within SUNY.

In addition, UB’s graduate programs in audiology (22) and speech language pathology (32) were also ranked this year.

Media Contact Information

David J. Hill Director of Media Relations Public Health, Architecture, Urban and Regional Planning, Sustainability Tel: 716-645-4651 [email protected]

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