Open Research Positions

Thank you for your interest in joining our research group!

Graduate students

We are taking on new PhD students each year.

If you are a current or a newly admitted PhD student excited about machine learning and/or applications in genomics, medicine, and health, please email Prof. Zitnik directly. Include your CV and a brief description of your research interests.

We are recruiting PhD students from a number of graduate programs, including Bioinformatics and Integrative Genomics, Systems Biology, Biological and Biomedical Sciences, Harvard Integrated Life Sciences, and other programs at Harvard. We also recruit graduate students from Health Sciences & Technology programs at Harvard and MIT.


Postdoctoral research fellow in AI/ML

We have an opening for a postdoctoral research fellowship in novel methods in the broad area of deep learning for graphs.

This position in available immediately. Interested candidates are encouraged to submit their applications as soon as possible.

NOW OPEN: Request For Applications


Postdoctoral research fellow in biomedical AI

We have an opening for a postdoctoral research fellowship in novel methods in the broad area of biomedical AI/ML.

This position in available immediately. Interested candidates are encouraged to submit their applications as soon as possible.

NOW OPEN: Request For Applications


Postdoctoral research fellow with Broad Institute of MIT and Harvard

The Eric and Wendy Schmidt Center (EWSC) at the Broad Institute of MIT and Harvard is seeking exceptional postdoctoral fellows to join the newly-launched center. The EWSC seeks to understand the programs of life and how they connect across biological scales–from the genetic to the cellular to the organismal–by creating a strong community at the interface of machine learning (ML) and biology.

CLOSED: Request For Applications

In the cover letter, include potential avenues of collaboration and supervision by Prof. Zitnik.


Postdoctoral research fellow with Harvard Data Science Initiative

The Harvard Data Science Initiative (HDSI) postdoctoral fellows are outstanding early-career researchers whose interests lie in a number of different fields. HDSI fellows work independently over a two to three year fellowship with the guidance and partnership of Harvard University faculty.

CLOSED: Request For Applications


Harvard/MIT undergraduates, Masters students, Harvard affiliates

On a rolling basis, we are looking for outstanding Harvard undergraduates, Masters students, and other Harvard affiliates. While we take students at all levels, excellent grades and/or prior experience in machine learning/AI is a plus. Generally, we expect:

  • Students commit to 15 hours per week to research (ideally more).
  • Students commit to at least 6 months of research with the lab (ideally more).
  • Prior experience in AI/ML and data science, which may include online courses. We encourage students to self-study relevant coursework. We provide mentoring on the very recent advances in the research field.

Please email Prof. Zitnik. Include your CV, current academic status, summary of research experience, and brief highlights of AI/ML-related projects.


Visitors, interns, and short-term students

We generally prefer visitors to stay for at least 6 months in order to carry out a high-quality research project.

Because of the large email load that Prof. Zitnik receives, she may not respond to all applicants. Please do not take this personally! We do review all applications!


Harvard is an Equal Opportunity/Affirmative Action Employer. Women and minorities are especially encouraged to apply.

Latest News

May 2022:   George Named the 2022 Wojcicki Troper Fellow

May 2022:   New preprint on PrimeKG

New preprint on building knowledge graphs to enable precision medicine applications.

Apr 2022:   Webster on the Cover of Cell Systems

Webster is on the cover of April issue of Cell Systems. Webster uses cell viability changes following gene perturbation to automatically learn cellular functions and pathways from data.

Apr 2022:   NASA Space Biology

Dr. Zitnik will serve on the Science Working Group at NASA Space Biology.

Mar 2022:   Yasha's Graduate Research Fellowship

Yasha won the National Defense Science and Engineering Graduate (NDSEG) Fellowship. Congratulations!

Mar 2022:   AI4Science at ICML 2022

We are excited to be selected to organize the AI4Science meeting at ICML 2022. Stay tuned for details. http://www.ai4science.net/icml22

Mar 2022:   Graph Algorithms in Biomedicine at PSB 2023

Excited to be organizing a session on Graph Algorithms at PSB 2023. Stay tuned for details.

Mar 2022:   Multimodal Learning on Graphs

New preprint! We introduce REMAP, a multimodal AI approach for disease relation extraction and classification. Project website.

Feb 2022:   Explainable Graph AI on the Capitol Hill

Owen has been selected to present our research on explainable biomedical AI to members of the US Congress at the “Posters on the Hill” symposium. Congrats Owen!

Feb 2022:   Graph Neural Networks for Time Series

Hot off the press at ICLR 2022. Check out Raindrop, our graph neural network with unique predictive capability to learn from irregular time series. Project website.

Feb 2022:   Biomedical Graph ML Tutorial Accepted to ISMB

Excited to present a tutorial at ISMB 2022 on graph representation learning for precision medicine. Congratulations, Michelle!

Feb 2022:   Marissa Won the Gates Cambridge Scholarship

Marissa Sumathipala is among the 23 outstanding US scholars selected be part of the 2022 class of Gates Cambridge Scholars at the University of Cambridge. Congratulations, Marissa!

Jan 2022:   Inferring Gene Multifunctionality

Jan 2022:   Deep Graph AI for Time Series Accepted to ICLR

Paper on graph representation learning for time series accepted to ICLR. Congratulations, Xiang!

Jan 2022:   Probing GNN Explainers Accepted to AISTATS

Jan 2022:   Marissa Sumathipala selected as Churchill Scholar

Marissa Sumathipala is selected for the prestigious Churchill Scholarship. Congratulations, Marissa!

Jan 2022:   Therapeutics Data Commons User Meetup

We invite you to join the growing open-science community at the User Group Meetup of Therapeutics Data Commons! Register for the first live user group meeting on Tuesday, January 25 at 11:00 AM EST.

Jan 2022:   Workshop on Graph Learning Benchmarks

Dec 2021:   NASA: Precision Space Health System

Human space exploration beyond low Earth orbit will involve missions of significant distance and duration. To effectively mitigate myriad space health hazards, paradigm shifts in data and space health systems are necessary to enable Earth independence. Delighted to be working with NASA and can share our recommendations!

Zitnik Lab  ·  Harvard  ·  Department of Biomedical Informatics