We pair machine learning engineers with medical students to tackle real clinical problems, guided by faculty physician mentors. Join us to lead high-impact independent research this summer with the opportunity to publish your work.
Many of medicine's biggest challenges are problems of data, prediction, and decision-making. Solving them requires both clinical intuition and technical fluency. But those two worlds often do not meet.
We created The Tensor Lab to address this. Our 10-week summer fellowship pairs talented machine learning engineers with medical students and practicing physicians to lead focused research. Fellows can work either independently or in small teams. The result is meaningful translational research.
This is a remote, project-based unpaid fellowship to train future innovators to design and lead medical research, from idea to execution. And they'll be in a cohort of equally driven, curious, and talented students to learn from. Successful projects will lead to academic publication and even influence how care is delivered to real patients.
You are the technical lead on the project, working alongside a medical student under the supervision of a fauclty physician. Ten to fifteen hours per week from June through August, remote.
A medical student who framed the research question and helps you interpret results. Coordinates with the faculty physician and translates between the clinic and your technical side.
A practicing physician and published researcher who sponsors the project, secures data access, and sets the scientific standard. Frequent check-ins with the team.
Key dates for Summer 2026. Application to final symposium in under five months.
Browse projects and apply to the ones you're interested in. Medical students will interview applicants and ultimately select the fellow to work on their team on a rolling basis.
Members of your team will get neccessary credentials and access to the tools they need to get started.
Build the model, run experiments, analyze results, and write the paper. This is the core of the fellowship.
Teams present their final work and research findings to the rest of the cohort, faculty advisors, and the broader community.
Teams are supported in pursuing academic communication of results, including presentations at conferences and peer-reviewed publications.
No. Your medical lead and faculty physician advisor provide clinical context. We are looking for strong Python, solid ML fundamentals, and curiosity about medicine. You will pick up the clinical side as you go.
Plan for ten to fifteen hours a week from June through August. Think of it like a serious research internship. If your circumstances shift, we can adjust.
Remote by default. You meet your team over Zoom or Slack. Some chapters organize optional in person working sessions if there is geographic overlap.
No. The fellowship is unpaid.
We default to open science. Code is open sourced and all team members share authorship. Patient data stays under the physician advisor's institutional controls.
We accept applications from current students, recent graduates, and career switchers with strong ML skills. The fellowship runs in the summer, but participation is not limited to people on academic calendars.
You rank three projects when you apply. If your first choice is filled before your application is processed, you stay in the running for your second and third choices. You will receive an email with a link to swap in a new choice if one of yours is filled.