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.
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
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.
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
Schmidt Center fellows are advancing machine learning’s potential to drive biomedical discoveries. Here’s what they're working on.
Gemma Moran, an alum of the Eric and Wendy Schmidt Center postdoctoral fellowship program, is working to improve the interpretability and transparency of machine learning models in medicine.
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Eric and Wendy Schmidt Center postdoctoral fellow Petar Stojanov receives a prestigious NIH grant to support his transition to heading his own lab.
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