Pre-Doctoral Fellow: Reinforcement Learning Scale Foundation Model Post-Training

Pre-Doctoral Fellow:
Reinforcement Learning for Large Scale Foundation Model Post-Training

Title
- Pre-Doctoral Fellow:
Reinforcement Learning for Large Scale Foundation Model Post-Training

School
- Harvard John

A. Paulson School of Engineering and Applied Sciences

Department/Area
- Computer Science

Position Description
- We invite applications for a Fellow to work with Assistant Professor Kianté Brantley  lab's research focuses on improving the capabilities of foundation models using reinforcement learning—from theory to practice. This position will emphasize large‑scale reinforcement learning for post‑training, studying both practical and theoretical issues pertaining to post‑training techniques. Successful candidates must be able to work as part of a team performing research to support the project.

Additional responsibilities include preparing publications and reports, mentoring graduate students, and collaborating with other groups. Successful candidates will be self-motivated, have a strong work ethic, be technically skilled, and have strong oral and written skills. Start dates are flexible, but the positions will be filled as soon as possible and will initially be for 6 months, renewable for an additional 6 months following performance review and funding availability.

Basic Qualifications - BA/BS in computer science, applied physics, applied math, or a related discipline.

Additional Qualifications
- Individuals with a demonstrated track record in scientific research, which can be evidenced through publications, technical reports, or impactful software projects.

Special Instructions - A complete application must include a curriculum vitae, 2–5 letters of reference, 2 publication samples, and a 1–2‑page research statement. In your cover letter, please also address the following supplemental questions: (1) What sorts of projects would you like to carry out in the lab? (2) What are your greatest strengths, and what areas would you like to improve?

Contact Information
- Anana Charles, Faculty Coordinator

Contact Email - acharlesvard.edu

Salary Range - $50,000 – $70,000 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 - 2

Maximum Number of References Allowed - 3

Keywords
- Machine Learning Reinforcement Learning Foundational Models Post-Training Large Language Models

EEO/Non-Discrimination Commitment Statement
- Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy.

Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.

Applicant Documents

• Curriculum Vitae
• Cover Letter
• Statement of Research
• Publication
• Publication 2
• List of References

• Publication 3