Up to 30% off — ends 2 Aug
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Up to 30% off — ends 2 Aug
ONLY00h00m00s
Panayiotis (Panos) Moutis
Closing soon
8 months ago
This position has expired. You can browse more openings on our positions listing pages.
PhD in Virtual Power Plant Battery Research at City College of New York (Electrical Engineering, Energy Modeling, Optimization) City College of the University of New York in United States
Degree Level
PhD
Field of study
not provided
Funding
Full funding availableDeadline
Aug 1, 2026
Country
United States
University
City College of the University of New York

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About this position
A fully funded PhD position is available in the Department of Electrical Engineering at the City College of the University of New York, focusing on Virtual Power Plant (VPP) battery research. The research aims to identify optimal battery chemistries and plan battery deployments for cost-effective load management among residential and small commercial US customers. The project seeks to improve utility programs and achieve at least 10% savings per household or business within five years, moving beyond traditional peak shaving to pragmatic coordination of services valuable to distribution systems through the VPP paradigm.
The successful candidate will join the DEgIDAL group and collaborate with Prof. Panayiotis (Panos) Moutis and Prof. Sanjoy Banerjee, as well as the CUNY Energy Institute. The position is part of the Translational Research Excellence Across Disciplines (TREAD) program funded by the US Department of Education. The PhD student will receive at least two years of guaranteed stipend at the highest NYC research assistant rate, plus additional funding for research supplies, core facilities, and travel to conferences and workshops.
Applicants must be US citizens or legal permanent residents (green card holders). They should demonstrate extensive expertise in energy modeling and electricity markets, a strong background in optimization and statistics (including Bayesian statistics, cone programming, and stochastic programming), and coding experience, preferably in artificial intelligence paradigms such as neural networks, decision trees, SVMs, clustering, or genetic algorithms. The position is open for Spring or Fall 2026 start.
To apply, contact Prof. Moutis via email with your CV and the subject line “(your name) – CCNY TREAD PhD opportunity”. For more information, refer to the TREAD program website and the detailed blog post linked above.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
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