Postdoctoral Fellow in Energy System Optimization and Digitization

Overview

Postdoctoral Fellow in Energy System Optimization and Digitization

Harvard John

A. Paulson School of Engineering and Applied Sciences (SEAS) and Harvard Business School (HBS) invite applications for a postdoctoral fellow to perform research on agentic AI, foundational modeling, optimization, and control of multiagent autonomous systems with applications in renewable energy and power grids. The fellow will work closely with Professors Le Xie and Christian Kaps and collaborate with graduate students and other researchers, including connections with the Salata Institute for Climate and Sustainability and the Climate and Sustainability Impact Lab at HBS.

Conduct research on agentic AI, foundational modeling, optimization, and control of multiagent autonomous systems in energy and power-grid contexts. Collaborate with graduate students and researchers on related projects. Engage with the broader Harvard community through affiliated institutes and labs.

Ph.D. in electrical engineering, applied mathematics, operations research, or a related field.

Strong mathematical background in reinforcement learning and/or control (e.g., optimal control, decentralized control, and/or adaptive control) with a demonstrated interest in energy and power grids. Substantial publication history, along with good teamwork and communication skills.

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 Email: jub
643vard.edu

Salary Range: $67,600 – $91,826. Pay offered 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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