HARVARD · STANFORD · MIT

Medical AI Bootcamp

A program for closely mentored research at the intersection of AI and Medicine. Open to Harvard, Stanford, and MIT students working in AI, and to medical doctors around the world.

Program

DURATION

6-9 months

HOURS / WEEK

15-20

MEETING TIME

11 AM-12 PM ET, weekdays

Students typically co-author manuscripts and frequently earn first-author positions.

Specializations

AI SPECIALIZATION

Stanford, Harvard, and MIT students
- Practical machine learning knowledge
- Python coding proficiency
- 2 semesters/quarters commitment
- Interview assesses programming skills
Undergraduates and graduate students welcome. We expect A grades in relevant coursework.
MEDICINE SPECIALIZATION

MDs or equivalent worldwide
- Medical degree (MD or equivalent)
- Clinical experience preferred
- Interest in AI applications
Particular interest in radiology specialists, but all specialties welcome.

Structure

MENTORSHIP

Direct mentoring from Prof. Pranav Rajpurkar with additional support from collaborating faculty, researchers, and postdocs.

RESEARCH

Students lead individual research projects with structured guidance and regular feedback.

MEETINGS

Weekly group Zoom meetings for progress updates, paper discussions, and skill development.

Recent Projects

Nature Biotechnology 2026 Vishwanatha M. Rao
Generalist Biological AI
Generalist biological artificial intelligence for modeling the language of life.
CHIL 2026 Minjia Wang

Clinically Grounded RL for Acute Care Notes

Open-ended clinical text generation for acute care, using reinforcement learning with clinically grounded rewards.
CHIL 2026 Xucheng (David) Wang
ReXSonoVQA
Video QA benchmark for procedure-centric ultrasound understanding.
MIDL 2026 (Oral) Roshan Kenia
ReX-MLE
Autonomous agent benchmark for medical imaging challenges.
CVPR 2025 Alice Heiman
FactCheXcker
Mitigating measurement hallucinations in chest X-ray report generation models.

In Their Words

The bootcamp provided an incredible opportunity to work on cutting-edge medical AI research. The mentorship was exceptional, and I was able to publish my first paper as a first author.

— Katherine Tian, Harvard Undergraduate

First-author publication, now Research Associate at Stanford
Working with the Rajpurkar Lab gave me hands-on experience with real clinical datasets and the skills to bridge AI and healthcare. The structured program helped me develop as an independent researcher.

— Kathryn Wantlin, Visiting Graduate Fellow

Now PhD Student at Princeton
The bootcamp accelerated my growth in machine learning while giving me exposure to impactful healthcare applications. The collaborative environment and weekly meetings kept me motivated throughout.

— Alyssa Huang, Harvard Undergraduate

Now Software Engineer at OpenAI

Apply

Applications reviewed on rolling basis monthly. Only candidates selected for interviews will be contacted.

REQUIRED MATERIALS

CV/Resume
Transcript (if available)
Written motivation statement

Application takes approximately 10-15 minutes.

Apply Now