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Doctor of Philosophy in Statistics (PhD)

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Established in 1983, the Department of Statistics at UBC is internationally renowned for its excellence in research and the high calibre of its faculty members. Our programs offers students different options for pursuing their interests and professional goals. Students completing our PhD program will be well-prepared for a job in industry, government or academia. During their program our students develop important professional skills that include: effective communication skills for both technical and non-technical audiences, creativity and originality, and grant writing skills, among others. They also acquire a broad knowledge of modern statistical methods, including computing and data management.

For specific program requirements, please refer to the departmental program website

What makes the program unique?

The Department is renowned in Canada for its research excellence and its leadership in the research community. Students are engaged through both courses and research, and develop a strong set of skills, both applied and theoretical. The Department has always valued data driven research, consulting and collaboration, and has long held communication and computing skills as crucial for success. Graduate students participate actively in our research, teaching and consulting activities, and enjoy a wide variety of opportunities for interaction with other researchers and students on- and off-campus. In addition, our graduate students run their own statistical consulting service, which provides them with professional (paid) experience even before they finish their program.

We have recently introduced a highly innovative qualifying process – instead of writing an exam, first year PhD students register in a reading and research course where they work on research papers proposed by individual faculty members.

UBC has a large number of research faculty working on a diverse array of projects and on interdisciplinary research. I feel that UBC offers the perfect environment for me to pursue my career goals and work on many interesting projects.

phd in analytics canada

Nikola Surjanovic

Quick Facts

Program enquiries, admission information & requirements, 1) check eligibility, minimum academic requirements.

The Faculty of Graduate and Postdoctoral Studies establishes the minimum admission requirements common to all applicants, usually a minimum overall average in the B+ range (76% at UBC). The graduate program that you are applying to may have additional requirements. Please review the specific requirements for applicants with credentials from institutions in:

  • Canada or the United States
  • International countries other than the United States

Each program may set higher academic minimum requirements. Please review the program website carefully to understand the program requirements. Meeting the minimum requirements does not guarantee admission as it is a competitive process.

English Language Test

Applicants from a university outside Canada in which English is not the primary language of instruction must provide results of an English language proficiency examination as part of their application. Tests must have been taken within the last 24 months at the time of submission of your application.

Minimum requirements for the two most common English language proficiency tests to apply to this program are listed below:

TOEFL: Test of English as a Foreign Language - internet-based

Overall score requirement : 100

IELTS: International English Language Testing System

Overall score requirement : 7.5

Other Test Scores

Some programs require additional test scores such as the Graduate Record Examination (GRE) or the Graduate Management Test (GMAT). The requirements for this program are:

The GRE is not required.

Prior degree, course and other requirements

Course requirements.

Successful PhD applicants typically have an MSc in Statistics or an MSc or PhD in Mathematics with strong evidence of interest in statistics. A student with only a Bachelors degree cannot usually be admitted to our PhD program, but rather must first enter the MSc program, either first completing the MSc or applying for transfer to the PhD after one year. If you have only had a few courses in statistics, your application to the PhD program will not be successful. For admission to the PhD program, the Admissions committee requires the following, in addition to the requirements for admission to the MSc program. a course in advanced statistical inference courses in rigorous mathematics at least 3 of the following courses at the graduate level: stochastic processes, advanced probability, mathematical statistics, linear models The above requirements are in addition to the minimum admission requirements of the Faculty of Graduate and Postdoctoral Studies. Please note that meeting our admission requirements does not guarantee admission. The following background will strengthen the application. courses in real analysis, and possibly measure theory, advanced probability (limit theorems, sigma fields); a broad range of courses in statistical methods (e.g., some topics among statistical computing, Bayesian statistics, generalized linear models, time series, multivariate statistics); undergraduate or graduate computer science courses; research or work experience relevant to statistics; solid programming experience (e.g., C, C++, Fortran, Python, R, SAS, Matlab).

Document Requirements

We require a 2 page (maximum) statement of interest/research proposal, as well as a CV.

2) Meet Deadlines

3) prepare application, transcripts.

All applicants have to submit transcripts from all past post-secondary study. Document submission requirements depend on whether your institution of study is within Canada or outside of Canada.

Letters of Reference

A minimum of three references are required for application to graduate programs at UBC. References should be requested from individuals who are prepared to provide a report on your academic ability and qualifications.

Statement of Interest

Many programs require a statement of interest , sometimes called a "statement of intent", "description of research interests" or something similar.

Supervision

Students in research-based programs usually require a faculty member to function as their thesis supervisor. Please follow the instructions provided by each program whether applicants should contact faculty members.

Instructions regarding thesis supervisor contact for Doctor of Philosophy in Statistics (PhD)

Citizenship verification.

Permanent Residents of Canada must provide a clear photocopy of both sides of the Permanent Resident card.

4) Apply Online

All applicants must complete an online application form and pay the application fee to be considered for admission to UBC.

Research Information

Research focus.

Faculty are conducting research in a variety of applied an theoretical areas, such as Bayesian Statistics, Bioinformatics, Biostatistics, Environmental and Spatial Statistics, Forest Products Stochastic Modeling, Modern multivariate and time series analysis, robust statistics, and Statistical learning. Further details can be found on our website: https://www.stat.ubc.ca/research-areas

Program Components

During the first year of the program, students will complete Stat 548, the Qualifying Course. This directed reading course consists of reading and reporting on five papers under the supervision of different faculty members. This unique course allows students the opportunity to explore a diverse range of Statistical topics and work with different faculty members before committing to a supervisor and thesis research topic. The PhD Comprehensive Exam will take place by the end of the second year in the program. This exam lays the groundwork for the PhD thesis, which consists of independent original research. Students are expected to have completed all required courses before the Comprehensive Exam. Near the end of thesis completion, students present their work at the Department Seminar.

Tuition & Financial Support

Financial support.

Applicants to UBC have access to a variety of funding options, including merit-based (i.e. based on your academic performance) and need-based (i.e. based on your financial situation) opportunities.

Program Funding Packages

PhD students in the Department of Statistics receive a minimum funding package of $24,000 for the first four years of the program. This funding comes in the form of teaching and/or research assistantships. Motivated students can often find additional sources of funding. Domestic students are expected to apply for NSERC PGSD scholarships. 

Average Funding

  • 17 students received Teaching Assistantships. Average TA funding based on 17 students was $13,833.
  • 26 students received Research Assistantships. Average RA funding based on 26 students was $17,379.
  • 10 students received Academic Assistantships. Average AA funding based on 10 students was $2,356.
  • 28 students received internal awards. Average internal award funding based on 28 students was $13,003.
  • 4 students received external awards. Average external award funding based on 4 students was $28,323.

Scholarships & awards (merit-based funding)

All applicants are encouraged to review the awards listing to identify potential opportunities to fund their graduate education. The database lists merit-based scholarships and awards and allows for filtering by various criteria, such as domestic vs. international or degree level.

Graduate Research Assistantships (GRA)

Many professors are able to provide Research Assistantships (GRA) from their research grants to support full-time graduate students studying under their supervision. The duties constitute part of the student's graduate degree requirements. A Graduate Research Assistantship is considered a form of fellowship for a period of graduate study and is therefore not covered by a collective agreement. Stipends vary widely, and are dependent on the field of study and the type of research grant from which the assistantship is being funded.

Graduate Teaching Assistantships (GTA)

Graduate programs may have Teaching Assistantships available for registered full-time graduate students. Full teaching assistantships involve 12 hours work per week in preparation, lecturing, or laboratory instruction although many graduate programs offer partial TA appointments at less than 12 hours per week. Teaching assistantship rates are set by collective bargaining between the University and the Teaching Assistants' Union .

Graduate Academic Assistantships (GAA)

Academic Assistantships are employment opportunities to perform work that is relevant to the university or to an individual faculty member, but not to support the student’s graduate research and thesis. Wages are considered regular earnings and when paid monthly, include vacation pay.

Financial aid (need-based funding)

Canadian and US applicants may qualify for governmental loans to finance their studies. Please review eligibility and types of loans .

All students may be able to access private sector or bank loans.

Foreign government scholarships

Many foreign governments provide support to their citizens in pursuing education abroad. International applicants should check the various governmental resources in their home country, such as the Department of Education, for available scholarships.

Working while studying

The possibility to pursue work to supplement income may depend on the demands the program has on students. It should be carefully weighed if work leads to prolonged program durations or whether work placements can be meaningfully embedded into a program.

International students enrolled as full-time students with a valid study permit can work on campus for unlimited hours and work off-campus for no more than 20 hours a week.

A good starting point to explore student jobs is the UBC Work Learn program or a Co-Op placement .

Tax credits and RRSP withdrawals

Students with taxable income in Canada may be able to claim federal or provincial tax credits.

Canadian residents with RRSP accounts may be able to use the Lifelong Learning Plan (LLP) which allows students to withdraw amounts from their registered retirement savings plan (RRSPs) to finance full-time training or education for themselves or their partner.

Please review Filing taxes in Canada on the student services website for more information.

Cost Estimator

Applicants have access to the cost estimator to develop a financial plan that takes into account various income sources and expenses.

Career Outcomes

31 students graduated between 2005 and 2013. Of these, career information was obtained for 29 alumni (based on research conducted between Feb-May 2016):

phd in analytics canada

Sample Employers in Higher Education

Sample employers outside higher education, sample job titles outside higher education, phd career outcome survey, career options.

Our students are prepared for a successful career in industry, academia or the public sector. Former students looking for a job after graduation have been promptly offered employment in many different industries, universities and government agencies. Please view a list of alumni and their first positions after graduation on our website.

Enrolment, Duration & Other Stats

These statistics show data for the Doctor of Philosophy in Statistics (PhD). Data are separated for each degree program combination. You may view data for other degree options in the respective program profile.

ENROLMENT DATA

Completion rates & times, upcoming doctoral exams, friday, 5 april 2024 - 9:00am - room 200, wednesday, 10 april 2024 - 12:30pm - room 200, wednesday, 17 april 2024 - 12:30pm - room 200.

  • Research Supervisors

This list shows faculty members with full supervisory privileges who are affiliated with this program. It is not a comprehensive list of all potential supervisors as faculty from other programs or faculty members without full supervisory privileges can request approvals to supervise graduate students in this program.

  • Auger-Methe, Marie (Fisheries sciences; Statistics; Zoology; Animal movement; Polar ecology; Statistical Ecology)
  • Bloem-Reddy, Benjamin (developing methods for evolving networks whose history is unobserved; distributional limits of preferential attachment networks; uses of symmetry in statistics, computation, and machine learning)
  • Bouchard-Cote, Alexandre (machine/statistical learning; mathematical side of the subject as well as in applications in linguistics and biology)
  • Campbell, Trevor (automated, scalable Bayesian inference algorithms; Bayesian nonparametrics; streaming data; Bayesian theory; Probabilistic Inference; computational statistics; large-scale data)
  • Chen, Jiahua (Statistics; empirical likelihood; finite mixture model; sample survey; asymptotic theory)
  • Cohen Freue, Gabriela (statistical genomics (focus in proteomics), robust estimation and inference, linear models with endogeneity )
  • Gao, Lucy (Statistics; Selective Inference; Inference x Unsupervised Learning; Statistics x Optimization)
  • Gustafson, Paul (Statistics; meta-analysis; Parametric and Non-Parametric Inference; Theoretical Statistics; Pharmacoepidemiology; Bayesian statistical methods; Biostatistics and Epidemiology; Causal inference; Evidence synthesis; Partial Identification)
  • Joe, Harry Sue Wah (Statistics; Statistics and Probabilities; copula construction; dependence modelling; extreme value inference; non-normal time series; parsimonous high-dimensional dependence)
  • Korthauer, Keegan (Bioinformatics; Genomics; Statistics; Epigenomics; Single-cell analysis; Statistical genomics)
  • McDonald, Daniel (High dimensional data analysis; Computational methods in statistics; Statistical theory and modeling; Machine learning; Epidemiology (except nutritional and veterinary epidemiology); Methods and models for epidemiological forecasting; Estimation and quantification of prediction risk; Evaluating the predictive abilities of complex dependent data; Application of statistical learning techniques to time series prediction problems; Investigations of cross-validation and the bootstrap for risk estimation)
  • Nolde, Natalia (Statistics; Statistics and Probabilities; Applications in finance, insurance, geosciences; Multivariate extreme value theory; Risk assessment)
  • Pleiss, Geoffrey (Statistical theory and modeling; Machine learning; Computational methods in statistics; Spatial statistics; Numerical analysis; Machine Learning; neural networks; Gaussian processes; Bayesian optimization; reliable deep learning)
  • Salibian-Barrera, Matias (S-regression estimationg, robust statistics, functional principal component analysis, bootstrap estimators, rgam, clustering algorithm)
  • Welch, William (Computational methods in statistics; Computer experiments; Design and analysis of experiments; Statistical machine learning; Environmental modellign)
  • Wu, Lang (Biostatistical methods; Longitudinal data analysis, mixed effects models, missing data, hypothesis testing, biostatistics)

Doctoral Citations

Sample thesis submissions.

  • Hidden at the root : statistical methods for population size estimation on trees
  • Conditional inferences and predictions based on copula models
  • Bayesian models for hierarchical clustering of network data
  • A data-driven ensemble framework for modeling high-dimensional data : theory, methods, algorithms, and applications : [supplementary material]
  • A data-driven ensemble framework for modeling high-dimensional data : theory, methods, algorithms, and applications
  • Boosting for regression problems with complex data
  • Design and analysis of computer experiments : large datasets and multi-model ensembles
  • Non-reversible parallel tempering on optimized paths
  • Inference under finite mixture models : distributed learning and approximate inference
  • Semiparametric inferences under a density ratio model

Related Programs

Same specialization.

  • Master of Science in Statistics (MSc)

Further Information

Specialization.

Research interests of the faculty include biostatistics, environmetrics, mathematical modelling of biological systems, computational statistics, data mining, machine learning, theory of statistical inference, asymptotics, multivariate analysis, robustness, nonparametrics, design of experiments, smoothing, Bayesian methods, computational molecular biology, gene expression, and microarrays.

UBC Calendar

Program website, faculty overview, academic unit, program identifier, classification, supervisor search.

Departments/Programs may update graduate degree program details through the Faculty & Staff portal. To update contact details for application inquiries, please use this form .

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Intelligent Systems and Data Science (PhD)

Faculty of Mathematics and Science PhD

phd in analytics canada

The PhD in Intelligent Systems and Data Science (ISDS) is a thesis-based program that targets the need for highly qualified scientists to tackle challenges in artificial intelligence & machine learning, integrated smart systems, modern software systems, statistical/mathematical modelling & analytics, and big data infrastructure.   

The program is offered jointly by the Department of Computer Science and the Department of Mathematics and Statistics .   

Graduates will proceed to research and/or teaching careers in academia, industry, government, and the community.  

Our Ph.D. in Intelligent Systems and Data Science is unique in many ways:

  • The degree title and focus areas are distinct throughout Ontario and Canada.
  • This interdisciplinary degree directly acknowledges the fundamental and intrinsic relationship between computer science, mathematics, and statistics.
  • The degree strives to foster a cohesive interdisciplinary program and community of students.
  • The qualifying examination requires students to write a research grant application. This experience will give students unique training in grant preparation.
  • The program allows students to gain experience in developing and applying advanced AI algorithms, complex software systems, data analytics tools, and statistical models.

For more information on Faculty Research, please visit the following pages: Computer Science Faculty Research Mathematics and Statistics Faculty Research

Entry point:

  • Thesis – 12 terms (4 years)

Application deadline:

General program inquiries Graduate program director Ke Qiu Graduate program coordinator Elena Genkin

Apply now Graduate Studies at Brock

Graduate calendar Tuition and financial information

Program website Faculty of Mathematics and Science

Admission requirements

  • Check the  university requirements  and the  program requirements.
  • Complete the  online application  and submit the non-refundable application fee.
  • Three academic references
  • Completed Statement of Research Interest that indicates potential supervisors
  • GRE Scores (general or math test) optional

Career outcomes

Research and Teaching careers where they can tackle challenges in artificial intelligence and machine learning, mathematical modeling and analytics, and big data infrastructures:

Research and Development Careers in Business and Industry where logical thinking, problem solving, and knowledge of qualitative methods are required:

  • Software Development
  • Information Technology
  • Startup companies
  • Business Intelligence
  • Insurances, Finances and Marketing
  • Medical and technological fields

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PhD in administration - Data Science

Phd in administration — data science.

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  • Tuition fees and Funding

Are you planning on a career in academia or business in the field of data science? Join a community of professors and researchers with valuable, recognized expertise.

Your PhD in short

  • Offered by HEC Montréal jointly with Concordia and McGill universities and the Université du Québec à Montréal (UQAM). This partnership gives you access to resources (faculty and courses) rarely available elsewhere in the world.
  • Full-time program allowing you to complete your studies in four or five years.
  • Tuition fees waived and competitive funding for the first four years of your studies.

For a fascinating career

Walid Mathlouthi

“Whereas many PhD programs aim exclusively at academic careers, HEC’s approach satisfies both academic interests and professional education.” Walid Mathlouthi, PhD. Data Science Consultant

marie-helene-roy

“The PhD program allowed me to build solid knowledge of data science methods that enables me to solve complex problems with rigor and success, and also to contribute to innovation in the industry.” Marie-Hélène Roy, PhD. Lead Data Scientist – Age of Learning, California

I - Ahlem Hajjem

“The teaching and support I received during my PhD studies at HEC Montréal were of such high quality that I couldn’t help but succeed.” Ahlem Hajjem, PhD. Professor at ESG UQAM

Among the best

The professors associated with this doctoral specialization have authored over 400 scientific papers in the top journals, including:

  • Bioinformatics
  • Journal of the American Statistical Association
  • Statistical Methods in Medical Research

Be part of research innovations

Ivado

Many of the professors in this specialization are members of MILA , Montréal’s world-renowned centre for artificial intelligence research.

Varied research interests

Methodology.

  • Artificial intelligence
  • Bayesian statistics
  • Big data mining
  • Data mining
  • Deep learning
  • Machine learning
  • Non-parametric methods
  • Recommendation systems

Applications

  • Analytics of urban environments
  • Network analysis
  • Traffic safety
  • User experience (UX)

Our PhD students and candidates

See the list of students in this specialization on Google Scholar

An exceptional research milieu

The eleven professors mainly associated with the doctoral specialization in Data Science have substantial research funds at their disposal to assist students. 

Eight of them hold chairs or professorships:

  • FRQ-IVADO Chair in Data Science: Professor Aurélie Labbe
  • Canada CIFAR Chair in Artificial Intelligence: Professor Laurent Charlin
  • Canada CIFAR Chair in Artificial Intelligence: Professor Jian Tang
  • Research Professorship in Complex Networks: Professor Gilles Caporossi
  • Research Professorship in Data Science: Professor Denis Larocque
  • Research Professorship in Statistics: Professor Debbie J. Dupuis
  • Professorship in Pedagogical Innovation in Active Learning of Statistics in Management: Professor Chantal Labbé
  • Professorship in Pedagogical Innovation in the Gamification of Learning for Data Science: professor Jean-François Plante

Marc Fredette is principal collaborator at the NSERC-Prompt Industrial Research Chair in User Experience .

Researchers in this specialization work closely with several research groups and knowledge transfer hubs, including:

  • Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT)
  • Centre de recherches mathématiques (CRM) (Mathematics research centre)
  • Group for Research in Decision Analysis (GERAD)
  • Montreal Institute for Learning Algorithms (MILA)

In addition, HEC Montréal is an institutional member of the Canadian Statistical Sciences Institute (CANSSI) .

  • 100% distance
  • Côte-des-Neiges
  •   Questions about our PHD Program?
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Rotman School of Management, University of Toronto

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The Rotman PhD Program

Join a close-knit community of scholars at one of the world’s top-ranked centres of management research – at the University of Toronto, in the heart of Canada’s vibrant, culturally diverse financial capital. As part of Rotman’s PhD program, you’ll explore new ideas, develop insights that inspire solutions and help to spark broader conversations among corporate and public leaders

  • Why Rotman?
  • Student Life

PhD PROGRAM - APPLICATIONS FOR SEPTEMBER 2024 ARE NOW CLOSED. Applications for Fall 2025 will be open in September 2024.  

The PhD in Management is a challenging 5 year program which features course-work, cutting edge research training, and close working relationships with some of the best management academics in the world.  The success of our program is evidenced in the impressive careers of our graduates.

PhD students work closely with faculty in our research-led culture which emphasizes rigor, creativity and innovation. The PhD curriculum is carefully designed to support students as publishing scholars as early as possible in their doctoral studies and we have a terrific track record of  placements in leading business schools. Our program is divided into 7 distinct streams of research: Accounting , Economic Analysis and Policy , Finance , Marketing ,   Operations Management and Statistics ,  Organizational Behaviour and Human Resource Management , and Strategic Management .

Questions? We Have Answers   Research What's Happening   PhD Courses @Rotman

The Rotman School is ranked 16th in the world by the Financial Times for its faculty and research. PhD students at Rotman enjoy an academic culture of collaboration and research excellence. Our doctoral program is delivered in seven streams that reflect the organization of the school as a whole: 

  • Economic Analysis and Policy
  • Organizational Behaviour and Human Resource Management
  • Operations Management and Statistics  
  • Strategic Management

PhD students at Rotman study in small classes and form close working relationships with faculty. Take a moment to get to know our program requirements. If you are a strong candidate with an appetite for academic excellence, we encourage you to contact us to learn more about the Rotman PhD.

Academics at Rotman Learn More    Research at Rotman See What's Happening

The Rotman PhD is for ambitious scholars who plan to teach and research at some of the world's top business schools. If you are looking to study with leading faculty, publish in noted academic journals, and build a global network of like-minded scholars, the Rotman PhD program is for you. Our goal is to prepare our PhD students for exceptional careers in the field of management, and all aspects of the doctoral program are developed with your professional goals in mind. Find out how the Rotman School at the University of Toronto has been the launching pad for many stellar academic careers.

Careers Learn More   Rotman PhDs on the Market   Research at Rotman See What's Happening

Are you a promising scholar driven to achieve success in your studies? At Rotman we believe that your success is fueled by support that extends well beyond scholarship. Your ability to achieve both during the program and after graduation depends on strong networks with faculty and your peers. We aim to give you the tools you need to complete your program while achieving a balanced life outside of the classroom. Explore these pages to relevant resources.

Student Life Learn More    Research at Rotman See What's Happening

Each year, the Rotman PhD program at the University of Toronto selects a small number of outstanding candidates who will go on to make significant contributions to management research and education. The admission selection process is highly competitive: on average only 15-20 doctoral students are admitted from a pool of 400-500 applicants. 

The faculty admission teams in each area look for excellent academic records that include strong backgrounds in relevant disciplines and/or previous work experience related to the intended area of concentration. Attention is also paid to test scores, letters of reference, and to the applicants' own written descriptions of their backgrounds, interests, and career goals. Explore these pages to learn about Rotman's highly competitive application process. 

Getting In Learn More   

The Rotman School of Management is accredited by the Association to Advance Collegiate Schools of Business (AASCB)

Graduate programs

In our Data Science programs, you will study the application and development of methods that facilitate insight from available data in order to understand, predict, and improve business strategy, products and services, marketing campaigns, medicine, public health and safety, and numerous other pursuits. 

Frequently asked questions (FAQ)

Funding and opportunities, admissions and applying, the waterloo advantage.

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Postdoctoral Fellow in Health Economics and Policy

. The fellowship is an opportunity for recent PhD graduates to sharpen their analytical skills and advance their research agendas in health economics and policy evaluation. This position is for a postdoctoral fellow

Sessional Lecturer-MHI2013H - Data Visualization in Health Care

enrolment: 30 Estimated TA support: based on enrolment – None Qualifications: PhD or Masters level education in health informatics or related field; A robust understanding of data visualization in health

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Postdoctoral Fellow - Wellington Laboratory

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. PhD degree in Mechanical Engineering, Structural Mechanics, Computer Engineering, Computer Science, or Statistics. Proven experience in a research setting, with a track record of successful publication

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Industrial PhD Position in Building Engineering

modelling building energy systems, and using at least one building simulation tool (e.g. Energy Plus, eQUEST, IESVE) Strong background in statistics, data analytics and machine learning, as well as linear and

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College Verdict

phd in analytics canada

The Top PhD Programs in Data Science in Canada

phd in analytics canada

Data science has been declared by Harvard Business Review to be one of, if not, THE most sexy jobs in modern times. With the rapid expansion of data and its importance in today's world, it's no wonder that universities are offering more and more programs dedicated to this field.

If you're looking to pursue a Ph.D. in data science, Canada is an excellent place to do it. Here are seven of the best universities for data science Ph.D. programs:

1. University of Toronto

2. McGill University

3. University of British Columbia

4. McMaster University

5. Université de Montréal

6. Western University

7. Queen's University

Best University for a Ph.D. in Data Science in Canada

There are many great universities in Canada that offer Ph.D. programs in data science. However, there is one university that stands out above the rest: The University of British Columbia.

The University of British Columbia offers a Ph.D. in data science that takes 5-6 years to complete. This program is highly respected and will give you the skills and knowledge you need to become a leading data scientist.

If you are looking for the best university for a Ph.D. in data science, then look no further than The University of British Columbia.

How Long Does it Take to Earn a Ph.D. in Data Science?

Data science is a relatively new field, and as such, there are not yet many data science Ph.D. programs available in Canada. However, for those interested in pursuing a career in data science, there are a few options available.

The average length of time it takes to complete a data science Ph.D. program is 4 years. However, some programs may take up to 9 years to complete. For students who want to complete their program in a shorter amount of time, some programs offer an accelerated option that can be completed in as little as 10 months.

Choosing the right data science Ph.D. program is an important decision that will impact your future career. There are many factors to consider when making your decision, such as the length of the program, the cost of tuition, and the location of the school.

If you're considering earning a Ph.D. in data science, make sure to do your research to find the program that's right for you!

The University of British Columbia

With over 65,000 students enrolled, The University of British Columbia is one of the largest universities in Canada. It's also one of the top-ranked schools in the world, coming in at 40th place according to Times Higher Education.

Of those 65,000 students, 17,000 are international students representing 140 different countries. UBC has campuses in both Vancouver and Okanagan in British Columbia, making it a convenient choice for students from all over Canada and the world.

UBC is especially well-known for its Computer Science program. The Ph.D. program offers research areas including Data Integration, Text Mining, Web Databases, and Optimization. The program is only offered as a full-time option and takes three to five years to finish.

If you're considering pursuing a data science degree at a Canadian university, UBC should definitely be on your list!

HEC Montréal

HEC Montréal is one of the leading business schools in Canada. Over 14,000 students attend the school founded in 1907.

The school is located in Montreal, Quebec, which is a great city for business and education. The Administration - Data Science PhD program at the school is a four to five year program.

This program is perfect for those who want to pursue a career in data science. The program provides students with the skills and knowledge they need to be successful in this field.

If you are interested in pursuing a career in data science, then HEC Montréal is the perfect school for you!

University of Waterloo

The University of Waterloo offers a Ph.D. in Computer Science with research areas relevant to data science, including databases, information retrieval, and machine learning. The program is offered in both full-time and part-time study modes, with admission three times per year.

Waterloo's computer science department is internationally recognized for its research excellence. In addition to the traditional areas of database systems, artificial intelligence, and software engineering, the department has strong research programs in human-computer interaction, graphics and visualization, networks, parallel and distributed systems, programming languages, security and privacy, theory of computation, and verification and testing.

The department offers a wide range of courses at the undergraduate and graduate level. Undergraduate students can choose from courses that cover the fundamentals of computer science as well as more specialized topics such as graphics or security. Graduate students can pursue their studies through coursework or research leading to a Master of Science or Doctor of Philosophy degree.

Waterloo provides an ideal environment for students interested in data science. The university is located in the heart of Canada's technology hub, where you'll have access to leading companies and organizations working with big data. And with world-renowned faculty members conducting cutting-edge research in data science, you'll be sure to get a top-notch education at Waterloo.

University of Alberta

The University of Alberta is a top-tier Canadian research university that was established in 1908. With Nobel-winning physicist Richard E. Taylor and former Canadian prime minister Joe Clark among its graduates, the total student enrolment at the university is over 40,000.

Alberta’s Department of Computing Science offers a Ph.D. in Computing Science with an extensive variety of research areas, one of which being data science. The Department of Mathematical and Statistical Sciences offers a Ph.D. in Statistical Machine Learning in collaboration with the Department of Computer Science.

Data science is an interdisciplinary field that combines aspects of computer science, statistics, and mathematics to extract knowledge and insights from data. It’s a relatively new field, but it’s growing rapidly in popularity due to the increasing amount of data being generated by businesses and organizations.

The University of Alberta’s Ph.D. in Computing Science program is designed for students who want to pursue careers in research and academia. The program offers a broad education in computing science, with coursework covering topics such as programming languages, software engineering, databases, and artificial intelligence. Students can also choose to specialize in specific areas such as data science or machine learning.

The Ph.D. in Statistical Machine Learning is a joint program between the Department of Computing Science and the Department of Mathematical and Statistical Sciences. This program is ideal for students interested in developing new methods for statistical machine learning, which is a subfield of artificial intelligence that deals with the design and development of algorithms that learn from data.

Both programs offer excellent preparation for careers in research and academia, as well as for positions in industry related to data science and machine learning. If you’re interested in pursuing a career in this rapidly growing field, either of these programs would be a great choice!

Dalhousie University

Dalhousie University, established since 1818, isone of North America's prestigiousolder institutions. Founded in 1818, it is located in Halifax, Nova Scotia. The school has a student population of around 19,000 and offers more than 180 programs at the undergraduate, graduate, and professional levels.

One of Dalhousie's most popular programs is its Ph.D. in Computer Science with a specialization in Data Analytics. This program prepares students for careers in data science and analytics, both in academia and industry. The curriculum covers topics such as machine learning, data mining, statistical modeling, and database management. Graduates of this program are well-positioned to pursue exciting and rewarding careers in a variety of fields.

University of New Brunswick

The University of New Brunswick was founded in 1785 and is located in Fredericton and Saint John, New Brunswick. It is the oldest English-language university in Canada and one of the first public universities in North America. There are over 10,000 students enrolled at UNB, which offers a Ph.D. in Computer Science with a focus on Data Management, Analytics, and Mining.

The program normally takes three years to complete, but students have the option of studying part-time if they meet certain conditions. Part-time students may take up to six years to complete the program. The average time to completion for full-time students is four years.

UNB's Faculty of Computer Science is one of the leading data science programs in Canada. The faculty has world-renowned researchers who are leaders in their field. The faculty is also home to the Canadian Institute for Cybersecurity, which is a world-class research centre that focuses on cybersecurity and data privacy.

In conclusion, there are many great universities in Canada that offer Ph.D. programs in data science. However, the University of British Columbia stands out as the best university for a Ph.D. in data science. The program is highly respected and will give you the skills and knowledge you need to become a leading data scientist. If you are looking for the best university for a Ph.D. in data science, then look no further than The University of British Columbia.

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Haskayne PhD

Haskayne PhD

A flexible, innovative and student-oriented approach

PhD students have the opportunity to make a significant and lasting contribution to the field of management. We provide a collaborative, supportive and intellectually stimulating research environment for the discovery and dissemination of knowledge applicable to the business community.

The Haskayne funding package is one of the most generous among Canadian business schools.

Additionally, scholarships, opportunities for publication and co-authoring articles in leading academic journals, and S upport to attend conferences in years two, three and four of the program is possible. Support is subject to approval prior to attending, and is contingent upon the student presenting at the conference.

We encourage early and continual involvement in research and give students the flexibility to explore topics of personal interest. Haskayne provides excellent supervisors who will work closely with you both in the classroom and on research projects, and provide essential resources and training in quantitative and qualitative methods and research design. A Haskayne PhD enhances communication skills, creativity, critical inquiry and confidence, in partnership with diverse professional networks and mentors.

Generous Funding

Flexible program.

The Haskayne PhD program is a full-time, research-intensive and highly flexible program that allows students to tailor courses to their needs and interests.

Outstanding Supervisors

All of our professorial faculty members are active researchers. Most are available to supervise students and work jointly with them on research projects.

Interested in learning more?

If you are interested in learning more about the Haskayne PhD program, application requirements and deadlines, please contact us.

Wondering if the Haskayne PhD is right for you?

Complete and submit this form for a quick assessment.

The University of Manitoba campuses are located on original lands of Anishinaabeg, Cree, Ojibwe-Cree, Dakota, and Dene peoples, and on the National Homeland of the Red River Métis. More

University of Manitoba

University of Manitoba Winnipeg, Manitoba Canada, R3T 2N2

Management (PhD)

The management PhD program is central to the mission of the Asper School of Business at UM. Students are mentored in their research program and in the development of teaching skills. Asper PhD graduates go on to fulfill the increasing need for Canadian-trained management academics.

Program details

Admission requirements.

• Asper School of Business • Stu Clark Graduate School • Faculty of Graduate Studies

• Doctor of Philosophy

Expected duration

Asper PhD student, Peter Pomart.

Experience the Asper difference

The PhD program is central to the mission of the Asper School of Business at UM. The program was founded in 1990 and our commitment reflects the increasing need for Canadian-trained management academics   The AACSB-accredited program has already fulfilled the expectations of students and faculty and continues to attract highly-qualified individuals who are interested in developing their research and teaching skills.

The PhD program in management is designed to produce graduates who have competitive research and teaching skills and the abilities necessary for placement in teaching positions in Canada and the world.

Expected duration: 4 years

Tuition and fees:  Tuition fees are charged for terms one and two and terms four and five. A continuing fee is paid for term three, term six and each subsequent term. (Refer to Graduate tuition and fees .)

Throughout their doctoral studies, students are engaged in research apprenticeships with the faculty. Students are assured of working with faculty members on several projects during their program and are required to spend a specific number of hours per week working for a faculty member during the term and in the summer. In this way, students are assured of receiving hands-on experience with the research process.

Students are expected to publish conference papers or journal articles during their program. Travelling to conferences and presenting research is a great way to meet other researchers in your field and gain exposure for your work.

Because the PhD program is designed for individuals who wish to pursue an academic career, a teaching practicum is required to help students develop teaching skills.

Program requirements

The PhD program consists of 30-39 credit hours of courses plus a thesis.

  • All PhD students must complete both core and other course requirements.
  • The core course are comprised of 12 credit hours (four courses) and are based on the student's departmental concentration area in the list outlined below.  
  • The core course requirements must be completed regardless of previous professional and/or academic background. (some of the other course requirements may be waived based on previous courses completed in a Masters program).
  • All students must complete PHDM 7140 Management Research Project 1 (a theoretical paper) and PHDM 7150 Management Research Project 2 (an empirical paper), both of which are zero credit, pass/fail courses.   
  • MKT 7110 Doctoral Seminar in Marketing
  • MKT 7120 Doctoral Seminar in Buyer Behaviour
  • MKT 7080 Research Design and Methods
  • MKT 7100 Selected Topics in Marketing

For full course descriptions, please visit the  Academic Calendar .

Business Administration

One (1) three (3) credit hour course from: 

  • GMGT 7410 Organizational Behaviour;
  • GMGT 7440 Organizational Theory; or, 
  • GMGT 7530 Strategy.

Three (3) additional three (3) credit hour courses from: 

  • GMGT 7440 Organizational Theory; 
  • GMGT 7410 Organizational Behavior; 
  • GMGT 7530 Strategy; or 

Topics courses in the area of organizational behavior, organization theory, strategy, entrepreneurship, international business, industrial relations and human resource management.

FIN 7700 Financial Economics FIN 7710 Empirical Asset Pricing FIN 7712 Seminar in Corporate Finance; and FIN 7714 Advanced Financial Theory

Supply Chain Management

Four of following courses are required:

  • SCM 7016 Simulation Models for Operations Management 
  • SCM 7018 Seminar in Production and Operations Management 
  • SCM 7020 Seminar in Supply Chain Management
  • SCM 7030 Doctoral Seminar in Supply Chain Sustainability 
  • MSCI 7550 Readings in Management Science
  • MSCI 7560 Doctoral Seminar in Management Science
  • MSCI 7680 Mathematical Optimization Models
  • OPM 7300 Topics Course

Other course requirements

Other course requirements (for all streams) may be required and could include:  

  • 1 Philosophy of Science in Management course PHDM 7110 (Note:  Finance students are exempt from this requirement) (3 credit hours);
  • 3 Methods or Statistics courses (9 credit hours; or up to 6 courses [18 credit hours] for Finance);
  • 2 minor/cognate courses (at least one of which is outside the Asper School of Business; 6 credit hours or up to 3 courses [9 credit hours] for Finance students)

Since students completing an Asper School of Business Ph.D. will be conducting research and teaching in topics related to management, they will be required to have a basic breadth of knowledge in management. Students with a previous business degree will not be required to complete this requirement, but students without a business degree will be required to audit at least one (1) and up to three (3) courses, preferably at the 7000 level, outside their core area in business.   

The following are minimum requirements to be considered for entry into the PhD in management program. Meeting these requirements does not guarantee acceptance into the program.

Those applying to the Asper PhD in management program should possess:

  • An earned Master's degree from a recognized institution in a management or business discipline, or in a cognate or foundational disciplinary area (e.g. psychology, sociology, economics, mathematics), with minimum 3.0 G.P.A.;
  • A minimum 600 GMAT score (or GRE equivalent);
  • English Language Test score, where applicable
  • Three letters of reference
  • Appropriate research interest and capability as evidenced by a statement of purpose; and,
  • A thesis from a recognized institution;
  • A major research paper from a recognized institution;
  • An independently completed research article published in a refereed journal;
  • An independently completed research working paper presented at a conference; and/or
  • Other evidence of an appropriate nature, such as written class research projects and term papers.

In addition to the admission requirements described here, all applicants must meet the minimum admission and English language proficiency requirements of the Faculty of Graduate Studies . 

How to apply

Applications for the PhD program are accepted once a year for Fall entry. Applications must be completed online and include several parts:

  • $100 application fee (non-refundable)
  • Unofficial copies of transcripts
  • CV or resume
  • Statement of intent
  • GMAT or GRE, with a minimum score of 600
  • 3 letters of recommendation from academic references
  • Proof of English language proficiency , if required

Please read the Faculty of Graduate Studies online application instructions before beginning your application.

GMAT and GRE resources

The Graduate Management Admission Test (GMAT) and Graduate Record Examinations (GRE) are standardized tests used to demonstrate academic qualification for graduate programs. Applicants to the Asper (PhD) must provide one of these test scores as part of the admissions process.

  • GMAT prep course
  • Register for GMAT
  • GRE prep course  
  • Register for GRE  

Application deadline

Applications are reviewed on a committee basis . The Admissions committee for Architecture reviews applications in March.

Applications open up to 18 months prior to start term.

Applicants must submit their online application with supporting documentation and application fee by the deadline date indicated.

Start or continue your application

Applications are reviewed on a committee basis . The Admissions committee for City Planning reviews applications in March.

Winter applications are accepted on a case-by-case basis.

Applications are reviewed on a committee basis . The Admissions committee for Design and Planning reviews applications in March.

Applications are reviewed on a committee basis . The Admissions committee for Interior Design reviews applications in March.

Applications are reviewed on a committee basis . The Admissions committee for Landscape Architecture reviews applications in March.

Applications are reviewed on a committee basis . The Admissions committee for Anthropology reviews applications in March/April.

Applications are reviewed on a  committee basis . Please contact the department for admission committee review timelines.

Applications open September 1 of year prior to start term.

Application deadlines

Applications open   up to 18 months prior  to start term.

Applications are reviewed on a  committee basis . The Admissions committee for History reviews applications in February.

Applications are reviewed on a  rolling basis .

Applications open July 1 of year prior to start term.

Applications are reviewed on a  Committee basis . The Committee for German and Slavic Studies reviews applications in February/March.

Applications are reviewed on a rolling basis .

Applications are reviewed on a committee basis . The Admissions committee for Management reviews applications in February / March.

Applications are reviewed on a committee basis . The Admissions committee for Physical Therapy reviews applications in April / May.

Applications open  August 1 of the year prior to start term.

Applications are reviewed on a committee basis . Please contact the department for admission committee review timelines.

Program currently undergoing review, applications will not be opening at this time.

Select Preventive Dental Science in the Program drop-down on the application form.

Applications are reviewed on a  committee basis . The Admissions committee for Educational Administration, Foundations and Psychology reviews applications in March / April.

Applications are reviewed on a  committee basis . The Admissions committee for Education reviews applications in February / March.

Applications are reviewed after the deadline, with decisions issued in March - April.

Currently not accepting applications to this program.

Applications are reviewed on a  committee basis . Please contact the department for admission committee review timelines.

Applicants must submit their online application with supporting documentation and application fee by the deadline date indicated. Applications received by the March 1 deadline for a September start-date will receive first consideration for any available funding. Late applications will be considered on a case-by-case basis for any available funding, please contact the department for further information.

Applications are reviewed on a  committee basis . The Admissions committee for Human Rights reviews applications in January - March.

Applications are reviewed on a  committee basis . The Admissions committee for Law reviews applications in January - March.

Applications are reviewed on a  committee basis . The Admissions committee for Nursing (MN) reviews applications in April / May.

Applications are reviewed on a  committee basis . The Admissions committee for Nursing PhD reviews applications in February / March.

Applications are reviewed on a  committee basis . The Admissions committee reviews applications as per the timelines noted below each table.

Winter applications reviewed in October Summer applications reviewed in February Fall applications reviewed in June

Winter applications reviewed in June Summer applications reviewed in October Fall applications reviewed in February

Applicants must submit their online application with supporting documentation and application fee by the deadline date indicated. This includes having the support of a faculty supervisor before you apply.

Applications are reviewed on a  committee basis . The Admissions committee for Natural Resources Management reviews applications in March - June.

After the annual application deadline (see below), applications are reviewed on a committee basis by the Faculty of Social Work internal admissions committee. Once this process is complete, decisions are sent to all applicants in March / April. 

Applications open  July 1 of year prior to start term.

Applications are reviewed on a  committee basis . The Admissions committee for Social Work reviews applications in March / April.

Applications are reviewed on a  committee basis . The Admissions committee for Music reviews Fall term applications in December / January, and Winter term applications in July.

Applications are reviewed on a committee basis . The Admissions committee for Occupational Therapy reviews applications in May / June.

Master of Occupational Therapy regular program  applications open September 15 of the year prior to deadline .

Master of Occupational Therapy accelerated program  applications open October 1  of the year prior to deadline .

The name of your confirmed supervisor is required at the time of application. To identify a prospective thesis research supervisor on your application, please  contact Immunology Faculty members .

Applications are reviewed on a  committee basis . The Admissions committee for Community Health Sciences reviews applications in March / April.

The name of your preferred supervisor is required at time of application.

Applications are reviewed on a  committee basis . Students selected for in-person interview will be notified in February.

Applications are reviewed on a  committee basis . The Admissions committee for Physician Assistant Studies reviews applications in April.

Offers of admission will be released to successful applicants on May 17, 2024 from the University of Manitoba Master of Physician Assistant Studies, the same day as the University of Toronto BScPA Program and McMaster University Physician Assistant Education Program. The three institutions are pleased to provide applicants their offers on the same day to help with the decision-making process.

Applications are reviewed on a  committee basis . The Admissions committee for Pharmacology and Therapeutics reviews applications one month after the application deadline.

Applications for Pathology MSc are reviewed on a  rolling basis .

Applications for Pathologist Assistant are reviewed on a  committee basis . The Admissions committee for Pathologist Assistant reviews applications in April / May. 

The Pathologist Assistant program only admits Canadian and US students every two years. The Fall 2023 intake has been suspended. The next intake is tentatively scheduled for Fall 2025.

Applications are reviewed on a  committee basis . The Admissions committee for Statistics reviews applications in March / April.

Applications are reviewed on a  committee basis . The Admissions committee for Biological Sciences reviews applications one month after deadline.

Applications are reviewed on a committee basis . The Admissions committee for Indigenous Studies reviews applications in February and June.

Applicants must submit their online application with supporting documentation and application fee by the deadline date indicated. For those who wish to be considered for scholarships, applications must be received by January 15 of the year in which you're seeking admission.

Applications are reviewed on a committee basis . The Admissions Committee for Applied Human Nutrition reviews applications in February.

Les demandes d’admission sont évaluées par un comité . Le comité d’admission évalu les demandes durant les mois de Mars et Avril.  

Les demandes peut être surmise jusqu’à concurrence de 18 mois avant le début de premier trimestre.

Toute demande d’admission en ligne doit être déposée, avec documents à l’appui, au plus tard aux dates indiquées.

Soumettre ou continuer votre application

Asper Career Development Centre

We provide students and alumni with career management skills needed to confidently embark on career exploration and long term career management.

Stu Clark Centre for Entrepreneurship

We support student entrepreneurship by being partners in education, driving entrepreneurial awareness and connecting students to the larger entrepreneurial ecosystem.

Tuition and fees

Learn about the tuition and fee requirements associated with graduate studies at UM.

Academic Calendar

Explore program requirements and detailed descriptions for required and elective courses throughout the Asper graduate programs.

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Explore the Asper School of Business

Taking our place among leading business schools we are committed to transforming research and scholarship, building a community that creates an outstanding learning environment, forging connections to foster high impact community engagement, and inspiring minds through innovative and quality teaching and learning.

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Explore the Faculty of Graduate Studies

Discovery happens here. Join the graduate students and researchers who come here from every corner of the world. They are drawn to the University of Manitoba because it offers the opportunity to do transformational research.

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More graduate programs

With over 140 programs across multiple faculties, schools and colleges, the University of Manitoba offers more learning, teaching and research opportunities than any other post-secondary institution in the province.

  • Master of Business Administration (MBA)
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  • Master of Art in Economics (MA)
  • MSc in Management

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Join the students and researchers who come here from every corner of the world.

What it's like to be a UM student

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Be adventurous, challenge yourself and make a difference.

Opportunities for Indigenous students

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Experience a world-class education in the heart of Canada.

Why international students study with us

The University Of Manitoba Fort Garry campus.

We offer state of the art facilities with 140 years of history.

Our campuses

Admission and application inquiries.

Faculty of Graduate Studies Room 500 UMSU University Centre 65 Chancellors Circle University of Manitoba (Fort Garry campus) Winnipeg, MB R3T 2N2 Canada

[email protected] Phone: 204-474-9377

Monday to Friday 8:30 a.m. to 4:30 p.m.

Program inquiries

Stu Clark Graduate School Asper School of Business Room 501, Drake Centre 181 Freedman Crescent University of Manitoba (Fort Garry campus) Winnipeg, MB R3T 5V4 Canada Phone: 204-474-6781 Email: [email protected]  Book an appointment

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McGill PhD in Management

McGill PhD in Management

McGill University is renowned for its academic excellence and continues to set the standard for higher education in Canada. 

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phd in analytics canada

Building excellence

The Desautels Faculty of Management at McGill, renowned worldwide for cutting-edge research , offers a PhD Program in Management where outstanding students conduct fundamental research at the frontiers of management knowledge and practice.

With the collaboration of faculty  and industry leaders, the program prepares students to become autonomous researchers, whose teaching, publications and consulting activities contribute to leading universities and organizations around the world.

The PhD program participates in a joint doctoral program that brings together the four leading Montreal universities (HEC-Montreal, Concordia, UQAM, and McGill).  As a result, students gain access to the rich doctoral offerings from other universities and are expected to include professors from other universities on their committees.

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Learn about the PhD experience from students and alumni

phd in analytics canada

Department and University Information

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McGill Desautels Faculty of Management

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  1. PhD In Data Analytics In Canada

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  2. How To Apply for PhD in Canada in 2024? Know About Requirements for PhD

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  4. Top Data Science & Analytics Colleges in Canada

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  5. PG Diploma In Business Analytics In Canada 2022: Top Colleges & Course

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  6. Top Colleges in Canada for Business Analytics 2020

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VIDEO

  1. EURO DOLLAR EXCHANGE RATE КУРС ЕВРО ДОЛЛАР 16.01.24 #shorts

COMMENTS

  1. 7 Universities in Canada with PhD in Data Science

    University of Waterloo. Next on our list of universities in Canada with a Ph.D. in Data Science is the University of Waterloo. Founded in 1957, the University of Waterloo (UWaterloo) has a student population north of 40,000. Around 20 percent of all undergraduate students and 40 percent of all graduate students have come from outside Canada.

  2. PhD

    PhD in Analytics. This specialization offers a wide variety of courses in Analytics, Operations Research and Operations Management to expose students to the latest methods, recent modeling approaches and current issues in the general areas of operations and decision making. ... Canada K7L 3N6. 1.877.533.2330. Toronto. Simcoe Place 200 Front ...

  3. Data Science, Analytics, and Artificial Intelligence

    The Data Science, Analytics, and Artificial Intelligence (DSAAI) master's and PhD programs are a natural extension of the popular Collaborative Specialization in Data Science that was launched in 2015 which is offered jointly by several departments. Data Science is a field which has grown in huge leaps. The Collaborative Specialization is ...

  4. Programs

    Programs. Our graduate programs incorporate elements of Statistics, Computer Science, and Optimization. The need for integrated graduate training across these disciplines is acutely felt across all industries. As one of Canada's most innovative universities, we aim to provide breadth and depth in all three of these areas as they pertain to ...

  5. Doctor of Philosophy in Statistics (PhD)

    Established in 1983, the Department of Statistics at UBC is internationally renowned for its excellence in research and the high calibre of its faculty members. Our programs offers students different options for pursuing their interests and professional goals. Students completing our PhD program will be well-prepared for a job in industry, government or academia.

  6. Intelligent Systems and Data Science (PhD)

    The program allows students to gain experience in developing and applying advanced AI algorithms, complex software systems, data analytics tools, and statistical models. For more information on Faculty Research, please visit the following pages:

  7. PhD in administration

    HEC Montréal is a founding member of the Institute for Data Valorization (IVADO). The Institute brings together 900 scientists interested in optimization (operational research) and data science. The group has received major funding ($93.6 million) for research into big data mining. HEC Montréal is home to Tech3Lab, the largest user-experience ...

  8. List of PHD Programs in Business Analytics in Canada

    Find the list of all PHD Programs in Business Analytics in Canada with our interactive Program search tool. Use the filters to list programs by subject, location, program type or study level.

  9. PhD

    Join a close-knit community of scholars at one of the world's top-ranked centres of management research - at the University of Toronto, in the heart of Canada's vibrant, culturally diverse financial capital. As part of Rotman's PhD program, you'll explore new ideas, develop insights that inspire solutions and help to spark broader conversations among corporate and public leaders

  10. Graduate programs

    Graduate programs. In our Data Science programs, you will study the application and development of methods that facilitate insight from available data in order to understand, predict, and improve business strategy, products and services, marketing campaigns, medicine, public health and safety, and numerous other pursuits.

  11. 144 data-analytics-phd positions in Canada

    Faculty of Science (Chemistry) Assistant Teaching Professor. University of Victoria | Victoria North, British Columbia | Canada | about 11 hours ago. stream with a proposed start date of September 1, 2024. A PhD in physical or analytical chemistry is required. The candidate's qualifications, experience and overall market demand will determine a.

  12. Scholarships for Data Analytics in Canada

    Reports can be generated based on the combination of data sets (like user profiles, statistics, market research, analytics data) regarding your interactions and those of other users with advertising or (non-advertising) content to identify common characteristics (for instance, to determine which target audiences are more receptive to an ad ...

  13. The Top PhD Programs in Data Science in Canada

    Founded in 1818, it is located in Halifax, Nova Scotia. The school has a student population of around 19,000 and offers more than 180 programs at the undergraduate, graduate, and professional levels. One of Dalhousie's most popular programs is its Ph.D. in Computer Science with a specialization in Data Analytics.

  14. Business PhD

    The Doctor of Philosophy in Business program at the University of Alberta offers specializations in Accounting, Finance, Operations and Information Systems, Marketing, and Strategy, Entrepreneurship and Management — including macro and micro organizational behaviour. At any given time, there are between 50-70 students, with an entering class ...

  15. PhD

    PhD students have the opportunity to make a significant and lasting contribution to the field of management. We provide a collaborative, supportive and intellectually stimulating research environment for the discovery and dissemination of knowledge applicable to the business community. The Haskayne funding package is one of the most generous ...

  16. PhD in Business Administration

    Driven by academic rigor, the UBC PhD program in Business Administration at UBC Sauder's Robert H. Lee Graduate School is defined by innovation. Our graduates are high-achieving, well-rounded scholars whose impeccable research skills have led them to ambitious intellectual pursuits. UBC Sauder PhD 85.7% of our grads have secured academic ...

  17. PhD in Operations and Information Systems

    PhD in Operations and Information Systems. OM is concerned with organizing the production of goods and services by private firms and public sector entities. OM research addresses questions about how best to design, plan and execute the tasks needed to produce a product or service. OM research has traditionally emphasized mathematical modeling ...

  18. PhD Study in Canada

    You can be confident that a PhD from Canada is well-respected. Attractive international fees - PhD study in Canada is generally cheaper than in the USA. Some universities actually reduce - or even waive - international fees. Post-study opportunities - Completing your doctorate will entitle you to live and work in Canada for up to three years.

  19. Management (PhD)

    The management PhD program is central to the mission of the Asper School of Business at UM. Students are mentored in their research program and in the development of teaching skills. ... Winnipeg, MB R3T 2N2 Canada. [email protected] Phone: 204-474-9377. Monday to Friday 8:30 a.m. to 4:30 p.m. Program inquiries. Stu Clark ...

  20. PhD Program in Management

    Building excellence The Desautels Faculty of Management at McGill, renowned worldwide for cutting-edge research, offers a PhD Program in Management where outstanding students conduct fundamental research at the frontiers of management knowledge and practice. With the collaboration of faculty and industry leaders, the program prepares students to become autonomous researchers, whose teaching ...

  21. PhD in Finance

    FIN 703: Advanced Seminar in Finance III. FIN 705: Research Seminar in Finance. Students must also complete at least two graduate level courses in finance, management science, or economics. The courses chosen must be approved by the student's supervisory committee and Associate Dean, PhD Program and may not count toward the cognate discipline.

  22. PhD in Marketing

    PhD in Marketing. In the broadest sense, marketing encompasses the entire system for bringing goods and services to actual and potential users. It includes understanding customer desires and then designing, distributing and informing potential customers of the means to satisfy these desires. Research in marketing may examine how a market ...

  23. PhD programmes in Business & Management in Canada

    Master in Business Administration (MBA)0. Master in Management (MIM)0. Operations and Quality Management0. Project Management0. Public Administration0. Retail Management0. Risk Management0. Strategic Management0. Supply Chain Management & Logistics0.