hiring

Join the Princeton RL group!

Because students from overrepresented groups are statistically more likely to apply [1, 2, 3], I especially encourage prospective students/postdocs from historically underrepresented groups to reach out.

• Post-bach, pre-doc, external, and visiting students: Apply by filling out this form.
• MS/PhD applicants: Apply to the Princeton MS and PhD programs through the department. Mention my name in your application if you’re interested in working together. Don’t email me reminders to look at your packet; rest assured that I will review every packet that mentions my last name. Useful resources:
  • Workshops on navigating the application process
  • Fee Waivers are available for many students.
  • Pre-application mentoring (scroll to bottom). Check out similar programs at other schools.
• Incoming Princeton PhD & MS students: If you’re an existing Princeton MS/PhD student interested in working together, send me an email.
• Princeton Undergrads: If interested in independent research, email me after taking either my graduate RL seminar or the undergraduate RL course.
• Postdocs: I am especially interested in working with a postdoc on (1) large-scale unsupervised RL, (2) connections between unsupervised RL (e.g., contrastive representations) and neuroscience (e.g., grid cells), and (3) applications of RL to synthesis problems in science/engineering. Funding for postdocs is currently limited, so I’d encourage prospective postdocs to apply for the Princeton Presidential Fellowship, the CSML Postdoc Fellowship, the PLI Postdoc Fellowship, or external postdoc fellowships. Apply by emailing me, including a resume, a few paragraphs about what you’d like to work on, and what fellowship[s] you plan to apply to (I can usually write a letter of support for these).
• High school students: I don’t work with high school students. Check out Princeton AI4All.

Tips:

• I am especially interested in recruiting students/postdocs with experience in (1) neuroscience + RL, (2) applications of control/planning/RL to science/engineering, or (3) large-scale GPU training.
• In your application, demonstrate that you understand the sorts of research that we’re doing (e.g., check our a recent talk or paper).