Join

We are a multi-disciplinary group, open to students in clinical and biomedical sciences, computer science, statistics, engineering, and related fields. We seek clarity and fairness from complex problems that necessitate interdisciplinary approaches. Our goals are to cultivate an environment for critical thinking, research creativity and open scientific collaboration. In addition, this lab is a good fit for those who wish to gain expertise in biomedical informatics and machine learning, especially when interpretability and fairness are central concerns. However, students are expected to already have some background in programming for data science, especially in R or Python.

Check out the opportunities below to get involved with the lab.

General Inquires

Email me with a description of your research, a CV, a sample publication (if applicable), and two reference contacts.

Postdoctoral Fellowships

• I am recruiting post-docs directly. Apply here: Postdoctoral Research Fellowship in Interpretable and Fair Machine Learning for Clinical Decision Support

• If you are a US citizen or resident, you may apply to this CHIP program: Postdoctoral Training in Informatics, Genomics, Machine Learning, Artificial Intelligence, Biomedical Data Science. It is best to contact me beforehand to discuss.

PhD Students

Current Harvard/MIT students: email me with a description of your research, a CV and two reference contacts.

Prospective students: consider these programs:

• https://hst.mit.edu/
• https://gsas.harvard.edu/admissions/apply
• https://dbmi.hms.harvard.edu/education/phd-program/ai-medicine-phd-track

Masters and Undergraduates

• Harvard students: please apply through the CHIP AI/ML internship program. If you would like to work with me, please indicate so on your cover letter.

• Check Harvard Catalyst for additional project descriptions.

• Otherwise, email me describing your interest, and include a CV and two reference contacts.