Post Doc in Learning, Optimization, and Control

Harvard University

United States

Postdoc Fellow in Learning, Optimization, and Control

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

Department/Area Electrical Engineering / Applied Mathematics / Computer Science

Position Description

Professor Na Li’s Lab in the School of Engineering and Applied Sciences (SEAS) at Harvard University seeks a motivated postdoctoral fellow with a Ph.D. in electrical engineering, applied mathematics, or any related field. Candidates who have a strong mathematical background in reinforcement learning and/or control (e.g., optimal control, decentralized control, and/or adaptive control) are preferred. Candidates will perform research on learning, optimization, and control of multiagent autonomous systems with a focus on theory development and algorithm design and analysis, in addition to working closely with graduate students and collaborators on research projects.

Basic Qualifications

Ph.D. in electrical engineering, applied mathematics, or any related field.

Additional Qualifications

Candidate should have substantial publication history, in addition to good teamwork and communication skills.

Special Instructions

A complete application must include a curriculum vitae, 2-5 letters of reference, three publication samples, and an optional 1-2 page statement of research.

SEAS is dedicated to building a diverse and welcoming community, and we strongly encourage applications from historically underrepresented groups.

Contact Information

Molly Marshall
Contact Email mmarshall@seas.harvard.edu

Equal Opportunity Employer

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.

Minimum Number of References Required 2

Maximum Number of References Allowed 5

Supplemental Questions

Required fields are indicated with an asterisk (*).

Applicant Documents

Required Documents
  1. Curriculum Vitae
  2. Publication
  3. Publication 2
  4. Publication 3
Optional Documents
  1. Statement of Research


In your application, please refer to Professorpositions.com

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