Postdoctoral Scholar - Computational Immunology

Stanford University
United States California Palo Alto


A machine learning postdoctoral scholar position is available at the Stanford University School of Medicine. No prior life science experience is necessary. The scholar will join a machine learning group with unparalleled direct access to clinical resources, as well as Stanford’s world-experts in machine learning and immunology. This is a unique opportunity for a machine learning scientist to directly impact patients’ lives in a clinical setting. Our research covers a wide range of unconventional yet high-impact topics ranging from space medicine to integration of mental health, physical health, immune fitness, and nutrition in various clinical settings. Particular areas of interest include pregnancy and neonatology, recovery from clinical challenges including stroke and surgery, as well as physical and biological aging.

Our group has a strong commitment to translating research findings to actionable insights and products with real-world scalability. We encourage (and financially support) our postdoctoral fellows to receive extensive training in entrepreneurship and business management from Stanford’s School of Business. This is an excellent opportunity for a candidate who is not only interested in participating in state-of-the-art academic research, but is also interested in exploring industrial and entrepreneurial career trajectories.

Diversity across all dimensions is not only a core value for our laboratory, but also is a key contributor to our innovative research. Applicants from groups traditionally underrepresented in computer science and machine learning are strongly encouraged to apply.


Relevant background:
-Ph.D. in a quantitative field
-Strong programming and statistics background
-Excellent publication and external funding track record
-Interest (but not necessarily expertise) in medicine and biology

Start date

As soon as possible

How to Apply

To apply, please submit a CV, a brief cover letter, and your response to the following question to


Nima Aghaeepour