Postdoctoral Fellowship in Reinforcement Learning, Probabilistic Methods, and/or Interpretability
Harvard University
Position
| Title | 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 Information | |
| 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 |
| Keywords |
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Supplemental Questions
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- Please list your research interests (200 character limit)
(Open Ended Question)
Applicant Documents
- Cover Letter
- Curriculum Vitae
- Statement of Research
- Publication
- Publication 2
- Other 2