We seek exceptional postdoctoral candidates hosted at UCSD Electrical and Computer Engineering, jointly advised by Prof. Yuanyuan Shi and Prof. Sujit Dey, to start as soon as possible.
With the growing adoption of construction electric vehicles (CEV), efficiently integrating mobile charging stations (MCS) into the power grid is crucial for sustainable electrification. This project focuses on developing optimization and learning-based methods to schedule mobile charging operations, reducing peak power demand, carbon emissions, and grid upgrade costs. The postdoc will lead research efforts, collaborate with industry and funding agencies, contribute to reporting and practical deployment of the intelligent charging infrastructure.
Qualifications
Ph.D. in Electrical Engineering, Computer Science, or Data Science (or related fields).
Hands-on experience and interest in system-level implementation and prototyping.
Strong background in optimization and solution algorithms, particularly large-scale integer programming.
Knowledge of Artificial Intelligence/Machine Learning is a plus.
Experience in battery and power grid modeling is a plus.
Strong communication, writing, and teamwork skills.
Application Materials
Curriculum Vitae (including publication list).
Cover Letter detailing motivation, research interests, and qualifications.
Names and contact information of three references.
(Optional) Research Statement (up to 3 pages) outlining past and future research relevant to this project.
How to Apply
Combine all application materials in one PDF file and send to "yyshi at ucsd dot edu" and copy sdey at ucsd dot edu with the subject line: "UCSD Prospective Postdoc [Your Name] - MCS4CEV"