Open Positions

Thank you for being so interested in joining our group! Successful career development in research requires quality mentoring relationships. Prof. Zitnik is the recipient of the 2022 Young Mentor Award at Harvard Medical School—this most prestigious award acknowledges that recognition to her.

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, 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 for cancer drug discovery

We have an opening for a postdoctoral research fellowship in novel machine learning approaches to cancer drug discovery.

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

NOW OPEN: Request For Applications


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 is available immediately. Interested candidates are encouraged to submit their applications as soon as possible.

NOW OPEN: Request For Applications


Postdoctoral research fellow with Harvard Data Science Initiative

The Harvard Data Science Initiative (HDSI) postdoctoral fellows are outstanding early-career researchers. 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’s students, Harvard affiliates

We are looking for outstanding Harvard undergraduates, Masters’s students, and other Harvard affiliates on a rolling basis. 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 20 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 may include online courses. We encourage students to self-study relevant coursework. In addition, we provide mentoring on the recent advances in the research field.

Email Prof. Zitnik. Include your CV, current academic status, a 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 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. Do not take this personally! We do review all applications!


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

Latest News

Jan 2023:   GNNDelete at ICLR 2023

Jan 2023:   New Network Principle for Molecular Phenotypes

Dec 2022:   Can we shorten rare disease diagnostic odyssey?

New preprint! Geometric deep learning for diagnosing patients with rare genetic diseases. Implications for using deep learning on sparsely-labeled medical datasets. Thankful for this collaboration with Zak Lab. Project website.

Nov 2022:   Can AI transform the way we discover new drugs?

Our conversation with Harvard Medicine News highlights recent developments and new features in Therapeutics Data Commons.

Oct 2022:   New Paper in Nature Biomedical Engineering

New paper on graph representation learning in biomedicine and healthcare published in Nature Biomedical Engineering.

Sep 2022:   New Paper in Nature Chemical Biology

Our paper on artificial intelligence foundation for therapeutic science is published in Nature Chemical Biology.

Sep 2022:   Self-Supervised Pre-Training at NeurIPS 2022

New paper on self-supervised contrastive pre-training accepted at NeurIPS 2022. Project page. Thankful for this collaboration with the Lincoln National Laboratory.

Sep 2022:   Best Paper Honorable Mention Award at IEEE VIS

Our paper on user-centric AI of drug repurposing received the Best Paper Honorable Mention Award at IEEE VIS 2022. Thankful for this collaboration with Gehlenborg Lab.

Sep 2022:   Multimodal Representation Learning with Graphs

Aug 2022:   On Graph AI for Precision Medicine

The recording of our tutorial on using graph AI to advance precision medicine is available. Tune into four hours of interactive lectures about state-of-the-art graph AI methods and applications in precision medicine.

Aug 2022:   Evaluating Explainability for GNNs

New preprint! We introduce a resource for broad evaluation of the quality and reliability of GNN explanations, addressing challenges and providing solutions for GNN explainability. Project website.

Jul 2022:   New Frontiers in Graph Learning at NeurIPS

Excited to organize the New Frontiers in Graph Learning workshop at NeurIPS.

Jul 2022:   AI4Science at NeurIPS

We are excited to host the AI4Science meeting at NeurIPS discussing AI-driven scientific discovery, implementation and verification of AI in science, the influence AI has on the conduct of science, and more.

Jul 2022:   Graph AI for Precision Medicine at ISMB

Jul 2022:   Welcoming Fellows and Summer Students

Welcoming a research fellow Julia Balla and three Summer students, Nicholas Ho, Satvik Tripathi, and Isuru Herath.

Jun 2022:   Broadly Generalizable Pre-Training Approach

Excited to share a preprint on self-supervised method for pre-training. Project website with evaluation on eight datasets, including electrodiagnostic testing, human daily activity recognition, and health state monitoring.

Jun 2022:   Welcoming New Postdocs

Excited to welcome George Dasoulas and Huan He, new postdocs joining us this Summer.

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.

May 2022:   Building KGs to Support Precision Medicine

Zitnik Lab  ·  Artificial Intelligence in Medicine and Science  ·  Harvard  ·  Department of Biomedical Informatics