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Postdoctoral Research Fellowships in the Science and Theory of Generative Modeling

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Harvard University

Harvard University, Cambridge, MA, USA

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Postdoctoral Research Fellowships in the Science and Theory of Generative Modeling

Postdoctoral Research Fellowships in the Science and Theory of Generative Modeling

Company:
Harvard University

Job Location:
Cambridge, 02138

Category:
Computer Science

Type:
Full-Time

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

Department/Area: Computer Science

Position Description

The John A. Paulson School of Engineering and Applied Sciences (SEAS) seeks applicants for two Postdoctoral Fellow positions in Assistant Professor Sitan Chen's research group, to work on topics in the science and theory of generative modeling, including (but not limited to): (1) diffusion language models, (2) reward tilting, (3) complexity of score estimation, and (4) sampling with advice.

Basic Qualifications

Candidates are required to have a doctorate or terminal degree in Computer Science or a related area by the expected start date.

Additional Qualifications

Candidates are expected to have a strong background in the foundations of machine learning.

Special Instructions

Required application documents include a cover letter, CV, a statement of research interests, and up to three representative papers. Candidates are also required to submit the names and contact information for at least three and up to five references, and the application is complete only when three letters have been submitted.

We encourage candidates to apply by April 1, 2026, but will continue to review applications until the positions are filled.

Contact Information

Allison Choat (Faculty Coordinator, Chen Group)

Contact Email: achoat@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: 5

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