Panayiotis Moutis
November 鈥25 (edited)
and I are recruiting one PhD student in the framework of the Translational Research Excellence Across Disciplines (TREAD) program funded by the Dept. of Ed (EDIT: TREAD website with more details about program priorities and framework ). Our work will focus on identifying battery chemistries and plan battery deployments for cost-optimal load management of residential and small commercial US customers. We aim to improve existing programs and yield savings of at least 10% per household or business in 5 years. We will go beyond the peak shaving practices and work on the pragmatic coordination of services valuable to distribution systems via the paradigm of Virtual Power Plants.
The PhD student will join the DEgIDAL group starting in Spring or Fall 26. DEgIDAL is part of the Dept. of Electrical Engineering (EE) at the City College of the (ranked behind the top world colleges in the value of the EE degree). The student will also be trained with Prof. Banerjee鈥檚 group and at the . The student receives at least 2-year guaranteed stipends (highest research assistant rate), and additional funding for research supplies/materials, core facilities fees and travel budget for conferences and workshops.
Successful applicants must demonstrate (via transcripts or peer-reviewed publications):
- extensive energy modeling and electricity markets expertise,
- strong optimization and statistical background (Bayesian statistics, cone programming, stochastic programming),
- coding experience (preferably in artificial intelligence paradigms such as neural networks, decision trees, SVMs, clustering, genetic algorithms).
The opportunity is open only to US Citizens and Legal Permanent Residents (green card).
For more information and to express your interest contact me via email with your CV and subject line 鈥(your name) 鈥 CCNY TREAD PhD opportunity鈥.