"Postdoc Fellow in Advanced AI for Energy/Power Grids"

Postdoc Fellow in Advanced AI for Energy/Power Grids

Company:
Harvard University

Job Location:
Cambridge, 02138

Category:
Electrical Engineering

Type:
Full-Time

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

Department/Area: Electrical Engineering / Applied Mathematics / Computer Science

Position Description
Professors Le Xie and Na Li in the John A. Paulson School of Engineering and Applied Sciences (SEAS) at Harvard University seek a motivated postdoctoral fellow with a Ph.D. in electrical engineering, applied mathematics, or related field.

Candidates will 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. This postdoctoral fellow will work closely with Professors Xie and Li while engaging with the broader Harvard community such as the Salata Institute for Climate and Sustainability, as well as the Kempner Institute.

Basic Qualifications

Ph.D. in electrical engineering, applied mathematics, or 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) with a strong desire to make an impact on energy/power grids are preferred.

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.

Contact Information

Roisin Dowling

Contact Email: rdowling@g.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