"Postdoctoral Fellowship in Reinforcement Learning, Probabilistic Methods, and/or Interpretability"

School: Harvard John A. Paulson School of Engineering and Applied Sciences

Department/Area: Computer Science

Position Description

Accepting applications for postdoctoral position in Reinforcement Learning, Probabilistic Methods, and/or Interpretability. Information on the lab can be found at finale.seas.harvard.edu and our group's webpage https://dtak.github.io/ We work on probabilistic models, reinforcement learning, and interpretability + human factors.

Basic Qualifications

Candidates are required to have a PhD in machine learning, math, stats, physics, or some other technical area by the time the position starts.

Additional Qualifications

Candidates should have significant experience in some area of statistical inference/optimization, and will have the chance to mentor both undergraduate and graduate students in these areas (as it relates to joint projects).

Special Instructions

Required application materials through this site include 2-3 recommendation letters, a statement of research interest, and a current CV.

Contact Email: finale@seas.harvard.edu

Salary Range

$67,600 - $91,826

*Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field.*

Minimum Number of References Required: 3

Maximum Number of References Allowed: 3

Apply Now