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Postdoc Fellow in Learning, Optimization, and Control
Harvard University in Cambridge, Massachusetts
Date Posted 08/14/2021
Admin-Tutors and Learning Resources
Employment Type
Application Deadline Open until filled

Title 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
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

*Please mention to employers when applying for this job*
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