Postdoctoral Fellow in Energy System Optimization and Digitization

Updated: about 15 hours ago
Location: Cambridge, MASSACHUSETTS
Deadline: ;

Details


Title Postdoctoral Fellow in Energy System Optimization and Digitization
School Harvard John A. Paulson School of Engineering and Applied Sciences
Department/Area
Position Description
Professor Le Xie in the John A. Paulson School of Engineering and Applied Sciences (SEAS) and Professor Christian Kaps in the Harvard Business School (HBS) at Harvard University seek a motivated postdoctoral fellow to perform research on agentic AI, foundational modeling,
optimization, and control of multiagent autonomous systems with an application in renewable energy and power grids, in addition to working closely with graduate students and collaborators on research projects. The postdoctoral fellow will work closely with Professors Xie and Kaps
while engaging with the broader Harvard community such as the Salata Institute for Climate and Sustainability, as well as the Climate and Sustainability Impact Lab at Harvard Business School.
Basic Qualifications
Ph.D. in electrical engineering, applied mathematics, operations research or related field.
Additional Qualifications
Candidates who have a strong mathematical background in reinforcement learning and/or control (e.g., optimal control, decentralized control, and/or adaptive control) with a strong desire to make an impact on energy/power grids are preferred. 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.
Contact Information
Justin Benton
150 Western Avenue, SEC 3.404
Boston, Ma 02134
Contact Email jub643@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 2
Maximum Number of References Allowed 5
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