The Medical AI Bootcamp provides Harvard and Stanford students an opportunity to do cutting-edge research at the intersection of AI and medicine. Over 6-9 months, members receive training to work on high-impact research problems in small interdisciplinary teams.
This bootcamp is a joint effort between Harvard and Stanford, and hosted virtually at the Rajpurkar lab.
New: Medical Doctors outside of Harvard and Stanford with an MD or equivalent can also apply to be part of the program.
We tackle important problems in medicine that require artificial intelligence solutions. We work on problems across clinical domains including radiology, emergency medicine, and cardiology, and develop computer vision and natural language processing solutions.
You tackle a scoped-out research project in a small team from conception to co-authoring a manuscript. You receive mentorship from faculty in team meetings on project execution and direction. You develop knowledge of cutting-edge medical AI research in reading groups, and machine learning tools in skills building sessions.
The bootcamp is fast-paced and highly collaborative. As a result, candidates are expected to be able to dedicate between 10-15 hours / week to the bootcamp over the course of the research project (typical time: 6-9 months), attending one large group meeting once a week and two smaller project meetings a week during the afternoons ET time.
Summer 2022 Cohort
Spring 2022 Cohort
Winter 2022 Cohort
We tackle important problems in medicine that require artificial intelligence solutions. You can see some of the projects we have worked on previously in the bootcamp or in its earlier iteration.
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports (Published in NeurIPS Datasets and Benchmarks 2021)
Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning (Published in Nature Biomedical Engineering, 2022)
Benchmarking saliency methods for chest X-ray interpretation (Published in Nature Machine Intelligence, 2022)
AI Specialization: Candidates with practical machine learning knowledge, and ability to code in Python; undergraduates and graduate students are expected to sign up for research credits for one semester or quarter. We actively seek and welcome candidates from historically underrepresented groups, candidates without previous research experiences, and candidates with primary fields of study outside STEM.
Medicine Specialization: The medicine specialization is open to medical doctors that have already received an MD or equivalent. In the upcoming round, we are especially interested in specialists in radiology and ophthalmology.
The medicine specialization welcomes candidates from around the country and world. The AI specialization is currently open for Harvard and Stanford affiliates only.
The applications for the next cycle are now open, starting Jan 9th 2023.
Early Applications due Oct 31st, 2022 at 11:59p PT.
Regular Applications due Nov 15th, 2022 at 11:59p PT.
Late Applications due Dec 15th, 2022 at 11:59p PT.
We will reach out to you if you are selected for the interview round.
We conduct rolling interviews and selections until the application deadlines.