computational biology phd harvard

In A Broader Scale of Inquiry

Center for Computational and Integrative Biology

About our center.

Faculty in the Center for Computational and Integrative Biology (CCIB) apply interdisciplinary approaches and new technologies to answer enduring biological questions and provide insights into human disease. Novel chemical, genomics and computational tools are developed to probe signaling pathways, identify mediators of host-microbe interactions, and design therapeutic disease interventions. Center investigators also conduct translational research to explore the potential utility of early-stage drug candidates in phase 1 studies carried out in small populations of individuals with the target disease indication. 

The CCIB provides support for investigators at Mass General Hospital and across the greater Boston area through a variety of autonomous cores that provide services in DNA sequencing, oligonucleotide synthesis and research laboratory automation. 

In the News

Welcome Jonathan Strecker, new faculty member in CCIB!  A main interest in the Strecker lab will be to investigate diverse immune proteins throughout nature, including phage defense and CRISPR-Cas systems, with the long-term goal of using these basic discoveries to enable new programmable functions in biology.

Congratulations Chris Smillie for being selected to join the  Pew Scholars Program in Biomedical Sciences ! The Scholars were chosen from 188 applicants nominated by leading academic institutions and researchers throughout the United States. This year’s class includes scientists who are studying how external and internal factors affect the gut microbiome, what causes HIV to re-emerge when treatment is halted, and how living an urban lifestyle affects long-term health.

Celebrating a historic $100M gift to establish the Gene Lay Institute for Immunology and Inflammation! The gift, from eminent biotechnology entrepreneur Gene Lay, founder and CEO of BioLegend, is the largest in Brigham's history. The  Gene Lay Institute  will be led by Vijay Kuchroo, an immunologist and principal investigator at the Brigham who will serve as inaugural director, Arlene Sharpe, chair of the Department of Immunology at HMS, and Ramnik Xavier, our Center Director. Areas of research will include basic understanding of immune-mediated diseases, aging, and cancer toward the development of new immunotherapies. The Institute will also provide training opportunities for students and fellows to support immunology innovators of the future.

Publications

Gut microbiome and metabolome profiling in Framingham heart study reveals cholesterol-metabolizing bacteria. Cell. 2024;:ePub

Translational genetics identifies a phosphorylation switch in CARD9 required for innate inflammatory responses. Cell Rep. 2024;43(3):113944

Hypoxia-inducible factor induces cysteine dioxygenase and promotes cysteine homeostasis in Caenorhabditis elegans . Elife. 2024;12:ePub

Hypoxia and intra-complex genetic suppressors rescue complex I mutants by a shared mechanism. Cell. 2024;187(3):659-675.e18

Trivalent rare earth metal cofactors confer rapid NP-DNA polymerase activity. Science. 2023;382(6669):423-429

Identification of host regulators of Mycobacterium tuberculosis phenotypes uncovers a role for the MMGT1-GPR156 lipid droplet axis in persistence. Cell Host Microbe. 2023;31(6):978-992.e5

Centenarians have a diverse gut virome with the potential to modulate metabolism and promote healthy lifespan. Nat Microbiol. 2023;8(6):1064-1078

Association of distinct microbial signatures with premalignant colorectal adenomas. Cell Host Microbe. 2023;31(5):827-838.e3

Genome-wide tiled detection of circulating Mycobacterium tuberculosis cell-free DNA using Cas13. Nat Commun. 2023;14(1):1803

Remodeling of colon plasma cell repertoire within ulcerative colitis patients. J Exp Med. 2023;220(4):ePub

The landscape of immune dysregulation in Crohn's disease revealed through single-cell transcriptomic profiling in the ileum and colon. Immunity. 2023;56(2):444-458.e5

Bacterial droplet-based single-cell RNA-seq reveals antibiotic-associated heterogeneous cellular states. Cell. 2023;186(4):877-891.e14

The Caenorhabditis elegans ARIP-4 DNA helicase couples mitochondrial surveillance to immune, detoxification, and antiviral pathways. Proc Natl Acad Sci U S A. 2022;119(49):e2215966119

Phase 2 Trial of Baxdrostat for Treatment-Resistant Hypertension. N Engl J Med. 2022;388(5):395-405

Engineered CRISPR prime editors with compact, untethered reverse transcriptases. Nat Biotechnol. 2022;41(3):337-343

NIN-like protein 7 transcription factor is a plant nitrate sensor. Science. 2022;377(6613):1419-1425

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The Harvard Biophysics Graduate Program

Phd research at the interface of quantitative science and biology.

HMS Campus, 240 Longwood Avenue, Seeley G. Mudd Bldg., Room 204c Boston, MA 02115

Theoretical & Computational Biology

Michael Baym, Ph.D. (He/ Him/ His)

Our lab studies microbial evolution, primarily of antibiotic resistance, with a goal of developing practical interventions to reduce or reverse resistance.

... Read more about Michael Baym, Ph.D. (He/ Him/ His)

Martha L. Bulyk, Ph.D. (She/ Her/ Hers)

Transcription factors and DNA regulatory elements.... Read more about Martha L. Bulyk, Ph.D. (She/ Her/ Hers)

George M. Church, Ph.D. (He/ Him/ His)

Pursuing "Next generation" DNA sequencing methods and chip-DNA-synthesis, gene editing and stem cell engineering. ... Read more about George M. Church, Ph.D. (He/ Him/ His)

Adam E. Cohen, Ph.D. (He/ Him/ His)

Physical tools to study molecules, cells, and organisms.... Read more about Adam E. Cohen, Ph.D. (He/ Him/ His)

Benjamin de Bivort

We study the neural circuit and molecular basis of individual differences in behavior using custom high-throughput instrumentation, with an eye to its ultimate cause in evolution. ... Read more about Benjamin de Bivort

Vladimir Denic

Molecular Principles Enabling Structural Diversification of Very Long-Chain Fatty Acids.... Read more about Vladimir Denic

Michael M. Desai, Ph.D.

We use both theory and experiments to study evolutionary dynamics and population genetics, particularly in situations where natural selection is pervasive.... Read more about Michael M. Desai, Ph.D.

Jan Drugowitsch, Ph.D. (He/ Him/ His)

Statistical computations and neuronal mechanisms underlying complex decisions and behavior under uncertainty.  The work in the lab is theoretical in nature, and we collaborate with experimentalists in a close loop to refine both theories and experiments.... Read more about Jan Drugowitsch, Ph.D. (He/ Him/ His)

Florian Engert

Neural circuits and behavior in larval zebrafish... Read more about Florian Engert

Lucas Farnung

The Farnung Lab is interested in molecular mechanisms at the interface of transcription and chromatin.... Read more about Lucas Farnung

Rachelle Gaudet, Ph.D. (She/ Her/ Hers)

Structural biology of signaling and transport through biological membranes.... Read more about Rachelle Gaudet, Ph.D. (She/ Her/ Hers)

Doeke Romke Hekstra

Sahand Hormoz

Sun Hur, Ph.D. (She/ Her/ Hers)

Our laboratory investigates the molecular mechanisms of the vertebrate immune system.

... Read more about Sun Hur, Ph.D. (She/ Her/ Hers)

Nancy Kleckner, Ph.D.

Chromosome Mechanics and Dynamics... Read more about Nancy Kleckner, Ph.D.

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Benjamin L. de Bivort

Faculty Support: Jennifer Thomson

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Michael M. Desai

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Scott V. Edwards

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John Wakeley

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Machine Intelligence Group for the betterment of Health and the Environment

Mauricio santillana, ph.d., director.

Network Science Institute, Northeastern University 177 Huntington Ave, Room 228, Boston, MA 02115

The Machine Intelligence Group for the betterment of Health and the Environment (MIGHTE), now based at the Network Science Institute , at Northeastern University  (from 2017 to 2022, our research lab, the Machine Intelligence Lab, was based at Boston Children’s Hospital) and the Center fo Communicable Disease Dynamics , at the Harvard T.H. Chan School of Public Health , has a multidisciplinary research agenda. Our research involves the conception and implementation of machine intelligence analytics tools, capable of predicting unobserved events in public health and healthcare in the immediate or near future. Our work ranges from tracking disease outbreaks around the Globe, leveraging information from big data sets from Internet-based services (such as Google, Twitter, Weather, Human Mobility, Electronic Health Records), to bed-side patient-centered monitoring approaches aimed at improving care in clinical settings.

Generally speaking, our approaches use machine learning techniques to identify patterns that have occurred historically that may be predictive of specific and future events of interest, for example:

• disease-related search activity on Internet search engines?
• the local air temperature/humidity in their location?
• human mobility patterns?
• multiple disparate Internet-based data sources ?
• Can we identify real-time vital signs patterns in a patient's hospital visit that may suggest the need to intervene or change care plans, hours (or days) before this happens?

Our team consist of applied mathematicians, computer scientists, physicists, public health experts, and clinicians. 

Current Team Members:

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MIGHTE News

• Professor Santillana and members of the MIGHTE team will participate in the  AI In Action   event held at Northeastern University in Boston on  April 4th.  Throughout the event, the team will showcase their research posters and take part in the session  'Beating the Next Epidemic with AI' .
• Team members Nicole Kogan and Mauricio Santillana presented their research and perspectives at the Workshop to Increase Diversity in Mathematical Modeling and Public Health on March 5. The event was organized by the CCDD, Harvard T.H. Chan School of Public Health, and the MIDAS Network Coordination Center. March, 2024
• Professor Santillana and members of the MIGHTE team participated in the inaugural in-person Epistorm general meeting held in Boston on February 28-29. Throughout the event, the team showcased their research posters and exchanged diverse perspectives on infectious diseases​. February, 2024
• Professor Santillana has joined the Steering Committee of the MIDAS Network 2024 . Models of Infectious Disease Agent Study (MIDAS) is a global network comprising scientists and practitioners who develop and employ computational, statistical, and mathematical models to enhance the understanding of infectious disease dynamics. February, 2024

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How to Become an Industry Computational Biologist in a Year

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Recently, MCS Advisors were able to attend the MassBioEd Life Sciences Workforce Conference where they discussed how the demand for the life sciences workforce in Massachusetts continues to grow, especially for those with interdisciplinary skillsets, like those of computational biologists. Read more in the 2023 Massachusetts Life Sciences Employment Outlook Report . Leveraging our Harvard network, we asked alumnus, Dean Lee, Compbio guru, to share his story, and insights into this exciting field.

In February of 2017, I was officially stuck. I was in my late 20s, I had been working towards academic science for eight years, but I had also just decided to take a gap year from my graduate neuroscience program at Harvard. Grad school made it clear to me that I would not be happy if I continued with academic science, so I was back at the drawing board. As lost as I felt, I knew that I wasn’t navigating completely blindly; I still enjoyed the life sciences, and I just needed to find a way to work on interesting biological questions beyond the confines of academia.

I knew only vaguely that I wanted to transition into computational biology (compbio). I noticed that data generation from biological experiments was becoming cheaper each year, but most biologists were not equipped to analyze this dramatically increasing amount of data. I guessed that if I could figure out how to analyze that data for them, then I can still work on exciting biological questions and maybe even get paid for it!

For the next 2.5 years, I struggled to acquire the necessary skills for becoming a computational biologist in the biotech/pharma industry. The bar seemed high; I wasn’t sure if or how I would learn enough programming, math, and statistics to be qualified. No one I spoke with could give me clear guidance on how to make this transition. I found many master’s programs that claimed to be a direct path to industry roles, but upon closer inspection most of them seemed to be money grabs that offered content that was too generic to be useful and training that was outdated (Ex. programming in Perl, analysis with Galaxy ). Even if some of those master’s programs were useful, I couldn’t afford them anyway. Eventually, I was able to navigate to my first industry compbio role, but only by trial and error. In retrospect, I probably could have made this transition in less than a year if I had proper guidance.

I hope to provide a bit more clarity to this process so you don’t have to spend as much time as I did groping in the dark. I will highlight several practical skills/experiences that will help you prepare for a compbio job (my examples will be a bit biased towards omics-related compbio). These components can be acquired simultaneously, and at any stage in your postsecondary education: bachelor’s, master’s, PhD, or postdoc. Those with more years of education might reasonably require less time to acquire these components, while those with fewer years of education might require more time.

1. Python and R (6 months- 1 year)

Want to know our little secret? Most industry computational biologists are not expert coders. I would be ashamed to admit how many for loops I write. Our product is not code; our product is biological insights we extract from data. We tend to perform ad hoc, highly customized analyses to answer niche questions. We are often superusers of a finite set of powerful Python/R packages that do all the heavy lifting for us in a particular domain of biology, rather than general programming maestros. We are very good at debugging by googling. We usually don’t need to code at the level of Google programmers.

With that in mind, your goal then is to become comfortable enough with Python and R such that you can quickly adopt any set of packages designed for biological data analysis. This familiarity should not require years and years of time. There are countless free online resources from which you can learn standard Python and R syntax. Start with one language, then eventually you can pick up the other. I personally think Python is the more efficient language and that compbio is slowly shifting towards Python. But for now many of the most popular packages for analyzing biological data are still in R, so it’s good to just learn both.

Make sure you learn how to make informative plots. Keep it simple. Boxplots, scatterplots, and heatmaps made with seaborn, matplotlib, or ggplot2 can go a long way.

2. Statistics (1 year)

I know machine learning is all the rage, but before you sink your teeth into the fancier techniques of machine learning, you should master the more traditional but still powerful approaches from statistics. Be very comfortable with foundational statistical topics/techniques such as probability theory, basic discrete and continuous distributions, hypothesis testing, p-values, multiple testing correction, various ways of normalizing data, measures of correlation, linear regression, logistic regression, principal component analysis, and cluster analysis.

Your standard year-long college-level statistics course series should do the trick. Many free online courses also will teach you well. Don’t just watch videos, however. Work out problems by hand so you learn these concepts deeply. Your future self will thank you.

3. Deep Understanding of a Field of Biology (1-2 years)

Industry computational biologists never work alone. We always work with bench scientists who generate the data we analyze. So we must speak their language. We need to understand the field in biology they are speaking from. We must understand why they designed their experiments a certain way, because it informs how we analyze their data. Being able to sympathize with the challenges faced by bench scientists also helps us to build positive working relationships with them. For this reason, experience as a bench scientist is highly relevant preparation for compbio roles. The better we can bridge the data-to-analysis-to-insight gap, the more valuable we are as computational biologists.

To gain deep understanding of a field in biology, read lots of primary literature in that domain. This is the most time-consuming piece of your preparation for a compbio role, but also the most fun! If you are a PhD student or postdoc in the life sciences, you should already have this skill; little to no further preparation is needed here. For undergrads and master’s students, please make sure that you learn how to dissect primary literature. It doesn’t matter how many or few biology classes you take; at the end of the day, you should be able to judge a Nature/Cell/Science article on its merits. There is no shortcut to learning this skill. You just have to sit down and read. Google is your friend. Joining a journal club can help. Your first scientific papers may take 10-20 hours each to digest.

One way to measure your ability to digest biology papers is to see whether you can pick up any Nature/Cell/Science paper in your chosen biological field and glean the gist of it in 15 minutes. You should be able to give an overview of the paper to a scientifically literate friend by drawing/writing on a single sheet of paper. The ability to do this implies you are familiar with the fundamental biology being addressed, the most popular/powerful experimental methods in that field, and the plots typically used to visualize results.

In addition to learning a field of biology, such as immunology or microbiology, we also have to follow the most recent technical advances in our own field of computational biology. New methods are published pretty much daily, and part of our jobs is to quickly decide which methods make sense and which do not. Having the ability to parse compbio primary literature will give you an additional edge in your preparation for an industry compbio role.

4. Compbio Project (3-6 months)

You need to complete a meaningful analysis of biological data as the final part of your preparation to become a computational biologist.

The most direct way to do this is to join a research lab that already has datasets you can play with. This might be imaging data, any kind of omics data (genomics, epigenomics, transcriptomics, proteomics) usually obtained by some sequencing approach (DNA-seq, RNA-seq, ATAC-seq), or data about DNA/RNA/protein structure. The variety of data types you might work with is too long to completely list here.

Mentoring matters a lot . Join a lab with a supportive graduate student or postdoc skilled in computational methods who can guide your data analysis. This person will save you countless hours banging your head against your MacBook when you are stuck. This person will also be your reference when you apply for a job.

Working on this project is where you specialize in certain compbio analyses. This often looks like becoming an expert user of certain Python or R packages designed to parse a specific type of data. You might find this blog by Tommy Tang, a personal hero of mine, helpful for some of your omics data analysis.

When you have completed your analysis, put it together into a PowerPoint presentation that tells a story in 30 minutes. You will need to convey the background on your chosen topic of study (Ex. mechanical sensation in developing fruit flies, mechanisms of resistance in gastric cancer), the exact questions/hypotheses you address, the data generated to test your hypotheses, the computational method used and why, any positive or negative findings, the implications of your findings for your field, any caveats in your data or analysis the audience should be aware of, and which experiments or additional analyses you propose to do next. Practice really does make perfect. Get lots of feedback from your research mentor.

If joining a research lab is not accessible to you, you might also complete your compbio project as part of an industry internship. For those who are extremely motivated, you could also complete this compbio project on your own free time by analyzing published data. For example, you might find this paper on synovial sarcoma interesting and decide to download the associated data here for your own analysis.

5. Apply and Interview!

Once you have your story, you are ready to start applying to compbio roles. This blog post by bitsinbio does a good job of broaching the variety of compbio roles; it is written for PhD-holders, but its content is helpful for job seekers at any stage in their education.

In your job search, you should be aware that there is a type of computational biologist for every flavor of biology. For example, a compbio role for evolutionary biology will share very few technical requirements with a compbio role for protein structure modeling, even though they may be advertised under the same job title. So read the job description closely to find out the skills required. Lots of nuances between compbio roles make it difficult for the hiring manager to identify the right candidate, so the more intentional candidate will be more successful in landing interviews.

If the data types and compbio analyses you specialized in for your compbio project are a match for the job description, you may get invited for interviews, which will typically involve 1) giving a short presentation on your project to showcase your scientific critical thinking abilities and technical skills and 2) one-on-one interviews with the hiring manager and your potential teammates to assess fit.

Most compbio jobs in the Boston area are hybrid; some WFH flexibility is the norm. Currently, the base salary for these industry compbio jobs are roughly $75-90K out of college , $80-110K out of a master’s , and $110-150K out of PhD/postdoc . The Broad Institute also hires many computational biologists, but their salaries are lower compared to their industry counterparts.

And there you have it! I hope that this general guide provides a bit more clarity to what it takes to work in computational biology and dispels some myths about entering this field. You don’t need to have years and years of advanced biology, statistics, computer science, and math training to begin meaningful contributions as a computational biologist.

I currently work as a computational biologist in Cambridge, MA. I am always open to connect with aspiring computational biologists at any stage in your education, so don’t hesitate to message me on LinkedIn .

About the Author: Dean started his graduate training in neuroscience (GSAS ’18) studying the molecular rules directing the developing mammalian cortex. But he decided to change course to computational biology as he witnessed the data revolution in the life sciences being accelerated by next-generation sequencing technologies. He now queries this data to guide immuno-oncology drug development in biotech/pharma. He thinks a lot about how scientists grow professionally and the organizational ingredients that enable scientists to realize their full positive impact on human health.

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The Harvard Biophysics Graduate Program

Phd research at the interface of quantitative science and biology.

HMS Campus, 240 Longwood Avenue, Seeley G. Mudd Bldg., Room 204c Boston, MA 02115

Dr. Steven A. Rosenberg, M.D., PhD. 1969 Graduate of the Harvard Biophysics Program, featured in the New York Times for his work on harnessing the immune system to fight cancer.

After a long, intense pursuit, researchers are close to bringing to market a daring new treatment: cell therapy that turbocharges the immune system to fight cancer. 

https://www.nytimes.com/2016/08/02/health/cancer-cell-therapy-immune-sys...

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Questions about these requirements? See the contact info at the bottom of the page. 

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Course requirements.

All first-year students are required to complete OEB399.

All courses must be taught by OEB faculty members or be courses in other departments approved by the OEB Graduate Committee. The grade minimum for graded courses is B-. OEB students must maintain a grade point average of at least a B (3.00) each academic year; the grade point average is weighted for each course based on the number of course credits. For example, a grade received in a two-credit course proportionally impacts the grade point average compared to a four-credit course. 

Students admitted in 2017 or later  are required to have completed four graded, four-credit courses by the end of their second year and a total of six graded, four-credit courses by the end of their third year. Students may fulfill up to two of these six total course requirements by teaching unique courses. For instance, a student who takes four graded courses and teaches two unique courses during their first three years would fulfill this requirement. A student can count a course once as a student and once (but not more than once) as a Teaching Fellow.  

For some students, specific courses may be prescribed by the OEB Graduate Committee. No student can be expected to have deep knowledge of all areas of modern biology, but all OEB graduate students are expected to have some familiarity with biological processes in (i) suborganismic (molecular and cellular biology), (ii) organismic (structure and function) and (iii) supraorganismic levels (evolution and ecology). Students are also expected to have competence in (iv) basic mathematics and statistics. Soon after their arrival at Harvard University, incoming students will meet with their advisor and members of the OEB Graduate Committee to review the student’s previous coursework, identify any gaps in basic knowledge, and develop a plan of study. If gaps are identified in any of the basic areas (i)–(iv), this plan of study will include prescribed courses to be completed by the end of the student’s second year with a grade of B- or better. All prescribed courses count toward the requirement for six graded four-credit courses. 

Students admitted prior to 2017 are required to have completed any prescribed courses by the time of their qualifying examination and a minimum of four graded courses by the time they defend their dissertation. With advisor approval, students may opt to take courses beyond their four-course requirement. The grade minimum for graded courses is B-. OEB students must maintain a grade point average of at least a B (3.00) each academic year; the grade point average is weighted for each course based on the number of course credits. For example, a grade received in a two-credit course proportionally impacts the grade point average compared to a four-credit course. 

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Teaching in the first year is not allowed per Harvard Griffin GSAS policy.

For students admitted in 2016 and later , the department requires at least three teaching fellow assignments for completion of the degree. Students must teach at least two different courses over at least two different terms. As part of your dissertation proposal for the qualifying examination, you should develop a teaching plan that will help you balance factors, including when courses of interest are being offered and when you might have a particularly intense field or laboratory work. 

Students admitted prior to 2016  are required to complete two teaching fellow assignments to meet the pedagogical requirement. 

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All students in the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences must be making satisfactory progress in order to be eligible for any type of financial aid. The following provisions are the interpretation of satisfactory progress for graduate students in OEB.

• During the first two years of graduate study, any student who is permitted to register is considered to be making satisfactory progress. OEB students are required to enroll and participate in OEB 399 in their first year.
• Students admitted in  2017 and later  must have completed four letter-graded courses (including all prescribed courses) and have taken the qualifying examination by the end of the second year. Students admitted  before 2017  are simply required to complete their prescribed courses and their qualifying examination by the end of the second year. Students can petition the OEB Graduate Committee to have their qualifying examination deferred until their third year. Such a petition takes the form of a written request to the director of graduate studies (DGS), endorsed by your advisor, and submitted during the second year. A deferral, if granted by the OEB Graduate Committee, does not change the requirement that a student who has not passed the qualifying examination by the end of their third year will be expected to withdraw. OEB students must maintain a grade point average of at least a B (3.00) each academic year; the grade point average is weighted for each course based on the number of course credits. For example, a grade received in a two-credit course proportionally impacts the grade point average compared to a four-credit course.
• Students admitted in  2017 and later  must have passed the qualifying examination and completed six letter-graded courses by the end of the third year. Students admitted  before 2017  must complete four letter-graded courses by the time they defend their dissertation.
• After passing the qualifying examination, students must hold a yearly dissertation advisory committee meeting and be judged to be making satisfactory progress.
• Students in their fourth year must participate in the G4 symposium in the spring.
• A student who is judged not to be making satisfactory progress may, with department endorsement, be placed on  grace status  for up to one year. Students on grace status remain eligible for financial aid during this period but cannot hold teaching appointments. At the end of the grace period, the student must have rectified the deficiency and be in compliance with all other established criteria in order to be considered to be making satisfactory progress. A student is ordinarily allowed only one period of grace.
• As noted above, the calendar of requirements may be interrupted by a single year of department-approved leave. In the particular case of a student who wishes to obtain a professional degree, the approved leave period can be extended beyond a single year.

Qualifying Examination

The qualifying examination is an oral examination conducted to assess whether the student has a well-designed research plan for their dissertation and to examine the student’s knowledge in broad areas of organismic and evolutionary biology. Students are expected to have taken the qualifying examination before the end of the second year of graduate study (exceptions may be granted by petition to the OEB Graduate Committee) and, at the very latest, to have passed the examination before the end of the third year of graduate study.

The qualifying examination committee consists of the student’s advisor and at least three other individuals. At least three committee members, including the chair,  must be members of the OEB faculty. Students should choose their committee chair (any OEB faculty committee member except their advisor) in consultation with their advisor. They should invite the chair to serve in that capacity when they invite them to serve on the committee. Students must obtain DGS approval of their qualifying examination committee and chair designation prior to submitting a notice of their examination to the senior academic programs administrator.

Students contact their committee to arrange an examination date and time. Three hours must be allotted for the meeting. Students should be aware that many faculty members may not be available when classes are not in session. Students are advised to remind faculty of the time and place of the meeting several days before the examination.

During the exam,  students will be tested on three broad topics pertinent to, but not restricted to, the specific topic of the proposed or ongoing dissertation studies. Topics should overlap a little and should be broad in scope. Students must obtain approval from the DGS for the three exam topics for these syllabi. After DGS approval, the student prepares a course syllabus outline for each topic. At least two of these courses should be modeled on a one-term lecture course meeting two to three times a week and addressing a broad area of biological knowledge. One course can be an advanced-level seminar on a more specialized topic. These syllabi will serve as a guide for the qualifying examination committee members to begin asking questions. However, committee members are not limited to asking questions directly relevant to the syllabi. Students are encouraged to meet with committee members before the examination to discuss questions that might be asked and to receive advice and recommendations on specific material that may be worth reviewing. There are no set guidelines on syllabus format; they should be modeled after those commonly distributed at the beginning of OEB courses. Students should consult with their advisor on the format.

The student is also expected to prepare a written dissertation   research proposal  for the qualifying examination committee.  Students should consult with their advisor about the format. In the examination, students will present a brief oral presentation on the proposal, designed to last approximately 15 to 20 minutes, not counting questions (recalling that committee members will have read the proposal so that it is neither necessary nor desirable to review everything in it).

The syllabi and dissertation proposal must be electronically distributed to qualifying examination committee members and the senior academic programs administrator at least two weeks before the examination. Failure to do so will result in the postponement of the examination .  

The qualifying examination committee chair will be in charge of the examination. At the outset, the student will be asked to leave the room so that the committee can discuss progress to date and ensure course prescriptions have been fulfilled. The advisor will then be asked to leave the room for the student to talk with the other committee members. After the advisor’s return, the student will then make their oral presentation, after which committee members will ask questions. Usually, committee members take turns, each asking several questions, with several rounds of questioning. At the end of the examination, students will again be asked to leave the room.

After the exam , students who passed the qualifying examination will be promptly notified and approved for the continuation of dissertation studies and advancement to doctoral candidacy. At least one term should ordinarily elapse between the qualifying examination and when the dissertation examination can be held. The qualifying examination committee may pass the student but prescribe additional coursework or other additional work (such as writing a review paper on a particular topic). Completion of this prescribed work is required before the next dissertation advisory committee meeting for the student to be judged at that time as making satisfactory progress.

If the qualifying examination reveals serious deficiencies , the committee may decide: (1) that the student be reexamined at a later date (but not later than the end of the G3 year) or (2) that the student not be admitted to candidacy for the doctoral degree. In the latter case, the committee will recommend that further candidacy be terminated not later than the end of the ongoing academic year. The recommendation to terminate must be reviewed and approved by the OEB graduate committee. The student, together with the advisor, may appeal any such decision by submitting to the OEB graduate committee written arguments for a reversal of the decision to terminate. Under such circumstances, the case will be further reviewed by the OEB graduate committee and the department before a final decision is rendered.

Dissertation Advisory Committee Meetings

Students have opportunities to review their dissertation project, its progress, and future potential with their dissertation advisory committee (DAC) in annual DAC meetings.  The first DAC meeting should be held no later than one year after the qualifying examination and at one-year (or shorter) intervals thereafter.  The student should present a brief account of any results obtained and plans for additional research. The DAC should indicate to the student whether it anticipates that the dissertation will be acceptable. It should also suggest improvement where needed. The DAC meeting is not intended to be an oral "examination,” but the DAC must approve the student’s progress and plans. If the DAC does not approve, then the student will be considered not to be making satisfactory progress, and a plan must be prepared to return to good standing within six months. Failure to do so may lead the DAC to recommend dismissal from the graduate program. Students more than six months late in holding a DAC meeting will automatically be considered not to be making satisfactory progress.

The DAC will consist of the student’s advisor and at least two other members. At least three members of the DAC must be OEB faculty. Additional members affiliated with other departments or institutions may be added after consultation with the advisor. Students should choose their DAC chair (any OEB faculty committee member except their advisor) in consultation with their advisor when they are assembling their DAC. The overall composition of the DAC must be approved by the DGS. The members of the DAC will, in most cases, also constitute the dissertation examination committee. In some situations, scheduling a meeting that all DAC members can attend may not be possible. With permission of the advisor and the DGS, one DAC member may be absent from the meeting, as long as arrangements are made for the student to meet separately with that DAC member. 

Dissertation Presentation and Examination

All graduate students in the Department of Organismic and Evolutionary Biology come under the jurisdiction of the OEB graduate committee. The DGS is authorized to approve all examination committees appointed for doctoral candidates.

1.  Application for the PhD Degree

Information on the degree  application is available on the  Harvard Griffin GSAS website . Students can find updated degree applications on the Harvard Griffin GSAS  Degree Calendar  and  Academic Calendar  pages. All applications must be approved by the DGS. Students should be aware that many committee members are not available for dissertation defenses when courses are not in session.

2.  Dissertation Presentation

The student must present the subject matter of the dissertation in a seminar open to the community and to which the members of the dissertation examination committee have been invited. This presentation shall take place prior to the dissertation examination. The senior academic programs administrator will send out notice of the public presentation to the OEB community two weeks prior to the date. A copy of the posted notice of the seminar will become part of the student's record.

3.  Dissertation Abstract

Each PhD candidate will prepare an abstract of the dissertation —ordinarily limited to one page, single-spaced—and submit it to the senior academic programs administrator two weeks prior to the date of the dissertation examination. Copies of the dissertation abstract will be distributed to the OEB community.

4.  Dissertation Examination

The  dissertation  is written under the supervision of the student's research advisor and should conform to the standards outlined in the Harvard Griffin GSAS policy page on  Dissertations .

The  Dissertation Examination Committee  will consist of the student’s advisor and at least two other members. At least three members of the committee must be members of the Department of Organismic and Evolutionary Biology. Additional members affiliated with other departments or institutions may be added by the advisor. As with the DAC, the committee chair must be an OEB faculty member who is not the student's advisor. The overall composition of the committee must be approved by the DGS. 

The senior academic programs administrator and the DGS must be notified of the  time and location of the dissertation   examination at least four weeks prior to the date  desired. The candidate must electronically distribute to their dissertation examination committee and the student academic programs administrator  their dissertation in final form at least 10 business days prior to the defense date .  Failure to electronically distribute the finalized dissertation to the dissertation examination committee and the senior academic programs administrator 10 business days prior to the exam date will automatically lead to postponement of the dissertation defense.

The student should observe the final dates for holding the dissertation examination indicated in the  Academic Calendar  posted on the Harvard Griffin GSAS website. It is strongly suggested that the dissertation examination be held at least one month prior to the dissertation electronic submission deadline to allow time for revisions; students should not expect committee members to approve a dissertation because a student has an impending deadline.

After examination, the dissertation examination committee will decide whether the candidate will pass, fail, or pass on the condition that specified changes be made to the dissertation (because students are often required to do additional work before the dissertation is passed, we recommend that students defend two to four weeks before degree filing or other deadlines). The dissertation examination committee may delegate to its chair the responsibility for seeing that such changes are made in a satisfactory manner before the award of the degree is recommended to the department by the graduate committee. The student's advisor should make such certification in writing to the DGS.

If possible, students should schedule their last DAC meeting one to three months before their dissertation defense. At this time, they should review the dissertation thoroughly, allowing committee members to identify issues that should be rectified prior to the presentation of the dissertation. Holding such a DAC meeting is the best way to ensure that problems are identified prior to the defense, thus minimizing the chance that the committee will require substantial additional work that may delay awarding of the degree.

In rare cases, it may be possible to hold the dissertation exam with one committee member absent. Arrangements must be made for that committee member to confer with the advisor prior to the dissertation being approved. Approval for such an arrangement must come from the DGS and only will be granted under unusual circumstances.

5.  Filing the Dissertation 

Students should consult the  dissertation submission guidelines . Each candidate must be registered in Harvard Griffin GSAS, with the required registration fee(s) paid, at the time the dissertation is filed, as summarized on the  Application for Degree  page. It is the student's responsibility to  electronically   via ProQuest ETD in accordance with the desired graduation date deadline.

Requirements for the AM Degree

The Department of Organismic and Evolutionary Biology does not admit students whose sole purpose is to study for the Master of Arts (AM) degree.

However, graduate students admitted to  any PhD program  at Harvard University or  OEB graduate students admitted prior to 2017 may apply for the AM degree if they fulfill the following requirements:

• Six letter-graded four-credit courses in the department (or other courses approved by the DGS), with no grades lower than B-. Students must maintain a grade point average of at least a B (3.00) each academic year; the grade point average is weighted for each course based on the number of course credits. For example, a grade received in a two-credit course proportionally impacts the grade point average compared to a four-credit course.  
• AM candidates must submit a written paper based on original research conducted under the guidance of a faculty member in the department. Both the student's advisor and the DGS must send the senior academic programs administrator their written approval of the paper.

OEB graduate students admitted in 2017 and later  may also apply to be awarded the AM degree. The requirements for students within the department are:

• Four graded four-credit courses by the end of their second year. In addition, students must either have completed a total of six graded four-credit courses by the end of their third year, or have completed four graded four-credit courses and acted as a Teaching Fellow in two additional courses by the end of their third year. All courses must be taught by OEB faculty members or be courses in other departments approved by the OEB graduate committee. The grade minimum for graded courses is B-. Students must maintain a grade point average of at least a B (3.00) each academic year; the grade point average is weighted for each course based on the number of course credits. For example, a grade received in a two-credit course proportionally impacts the grade point average compared to a four-credit course.  A student can count a course once as a student and once (but not more than once) as a Teaching Fellow.  All prescribed courses count toward the requirement for six graded four-credit courses.
• A written report based on original research conducted under the guidance of a faculty member in the department (the student’s dissertation proposal will often satisfy this requirement). The student's advisor and the DGS must send the senior academic programs administrator their written approval of the report.

Contact Info

Organismic and Evolutionary Biology Website

Explore Events

Thesis Defense – Jiaxin Shen

May 8 @ 1:00 pm - 2:30 pm.

Jiaxin will present the thesis entitled “Unsupervised Model Aggregation Methods to Integrate Pre-trained Polygenic Risk Prediction Models”. The thesis committee is chaired by Dr. Rui Duan, and includes Dr. Georg Hahn and Dr. Erin Lake.

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