Fellowship Program

We train the next generation of machine learning leaders who drive biological discovery.

The Eric and Wendy Schmidt Center brings together a wide range of researchers to identify key challenges; generate new kinds of data; create novel theoretical, computational, and algorithmic paradigms — and apply these insights to solve the most pressing problems of biology and medicine.

Postdoctoral Fellowship

We fund postdoctoral associates with research interests in any area of machine learning, statistics, or applied mathematics that could drive the frontier of biomedical research. Postdocs choose a computational and biomedical mentor from Broad-, MIT-, or Harvard-affiliated faculty.

  • One-year appointment with the possibility of renewal for a second and third year based upon satisfactory performance

  • Experience in machine learning or related fields is critical for the role, while prior exposure to biology or medicine is helpful but optional

Application portal opens late fall

Review period starts December 20

Fellowship start date is flexible

Postdoctoral contact form

Who We Are

The Schmidt Center was established to unite the disciplines of machine learning and biology to realize the promise that rests in unlocking a greater understanding of the most pressing questions in the life sciences. We seek to achieve our mission through three guiding pillars: (1) supporting research at the intersection of machine learning (ML) and biology; (2) developing a robust community that is globally based; and (3) training the next generation of leaders that will be fluent in both fields.


Research Environment

  • Embedded in a world-class research community at the Broad Institute

  • Mentorship from computational and biomedical researchers across the Broad, MIT, and Harvard

  • Become part of a highly collaborative and active center with regular talks, group meetings, coffee socials, and other events at the nexus of machine learning and biology

  • Access to high-end computing resources

Meet Some of Our Fellows

Schmidt Center fellows are advancing machine learning’s potential to drive biomedical discoveries. Here’s what they're working on.

Caroline Uhler, Schmidt Center director, named IMS Fellow

The Institute of Mathematical Statistics (IMS) fosters the development and dissemination of the theory and applications of statistics and probability.

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How do neural networks learn? A mathematical formula explains how they detect relevant patterns

The insights, published in the journal Science, can also be used to make other types of machine learning architectures more effective.

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Data science challenge reveals new research directions for cancer immunotherapy

More than 1,000 people registered for the challenge, which harnessed machine learning to predict ways to make T cells better cancer-cell killers.

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Join Us!