Overview

Prof. Marinka Zitnik invites applications for a Postdoctoral Research Fellowship position at Harvard University.

This is an exceptional opportunity to advance the field of medical AI through cutting-edge research in generative AI and its transformative applications in precision medicine and health systems.

The successful candidate will lead research projects that aim to shape the future of medical AI. Potential research directions include:

• Patient-centric generative AI to advance precision medicine and deliver tailored treatments for diverse patient populations.
• Dynamic representations of evolving medical knowledge to bridge the gap between scientific discoveries and rich patient datasets.
• Integration of large language models and medical knowledge graphs to unify biomedical data, reduce uncertainty, and enable actionable predictions.
• Multimodal AI for global health decision-making to develop reliable, agentic AI systems and knowledge graph-powered LLMs for clinical support, rooted in global, country-specific, and context-appropriate medical guidelines.

This position offers unique opportunities for collaboration with global research foundations, patient-led organizations, and international health systems, fostering a truly interdisciplinary and impactful research environment.

Interested candidates are encouraged to explore our recent publications and research directions before submitting their applications.

Qualifications

We are seeking highly motivated applicants with expertise in one or more of the following areas: agentic AI, large language models, large-scale knowledge graphs, medical foundation models, multimodal learning, and generative AI. Strong technical skills and prior experience in precision medicine are essential.

Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading medical journals.

Candidates must hold a Ph.D. or equivalent degree in machine learning, computer science or a closely related field.

This position involves close collaboration with global research foundations, patient-led organizations, and international health systems. Strong communication skills and experience working in interdisciplinary teams are highly desirable.

Excellent programming skills and practical experience with leading machine learning frameworks are required. Applicants must have experience applying AI to medicine. Familiarity with modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds of GPUs, is a significant advantage.

Application process

The position is available immediately and can be renewed annually. Interested applicants should submit the following documents via email to Prof. Zitnik and use the subject line “Postdoctoral Research Fellows in Medical AI”:

• Curriculum Vitae (include links to your academic webpage and GitHub repositories for methods you developed)
• Three representative publications (preprints are acceptable)
• Statement of research (two pages) describing prior research experience and future research plan
• Contacts for three letters of recommendation (the letters will be solicited after the initial review)

We are currently reviewing applications. Interested candidates are encouraged to submit their applications early.

Advisor

Marinka Zitnik is an Associate Professor of Biomedical Informatics at Harvard Medical School, Associate Faculty at Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, and Associate Member at Broad Institute of MIT and Harvard. Zitnik investigates foundations of AI that contribute to the scientific understanding of medicine and therapeutic design, eventually enabling AI to learn and innovate on its own. Her research won best paper and research awards, including the Overton Prize, Kavli Fellowship of the National Academy of Sciences, Kaneb Fellowship award at Harvard Medical School, NSF CAREER Award, awards from the International Society for Computational Biology, International Conference in Machine Learning, Bayer Early Excellence in Science, Amazon Faculty Research, Google Faculty Research, Roche Alliance with Distinguished Scientists, and two Sanofi iDEA-iTECH Awards.