SPEL invites applications for multiple Ph.D. positions and at least three Postdoctoral Research Associate positions starting in early September 2024. These positions are central to the technical leadership and advancement of the TRANSFORMATIVE project, which was recently funded by the Department of Energy.  The selected candidates will be working on the TRANSFORMATIVE project, with a focus on developing advanced time-series optimization methodologies for power system optimization and resilience, specifically enhancing T&D coordination and integrating VRE/DER capabilities into grid operation.

Selected candidates will be responsible for:

• Manage the TRANSFORMATIVE project, to ensure successful delivery and execution of specified tasks and milestones;
• Collaborate closely with industry partners, national laboratories, and software vendors to co-lead the project towards achieving its goals;
• Assist in writing and publishing quarterly progress reports and contributing to top-tier journal publications in the field;
• Manage and contribute to the project’s open-source codebase on GitHub;
• Engage in collaborative research activities, promote innovation and knowledge exchange within and beyond the project team; and
• Contribute to the development of project workshops, seminars, and webinars for disseminating new research findings and promoting community engagement.

Qualifications:

• A PhD degree (or near completion for post-doctoral applicants) or M.S. degree (for Ph.D. applicants) in Electrical Engineering or a closely related field, with a strong and specific focus on power system optimization, AC Optimal Power Flow (ACOPF), unit commitment, T&D system modeling, and grid resilience;
• Expertise in programming languages such as Python, C++, or Julia, and optimization software such as Gurobi. Proficiency in Julia will be considered additional credit;
• Solid experience with GitHub and version control practices;
• Exceptional analytical and problem-solving skills, with a track record of innovative research and publication in top-tier journals;
• Experience in applying machine learning technologies in the optimization and grid operation is additional credit;
• Excellent communication skills, with the ability to articulate complex technical concepts to a broad range of audiences, including with DOE program managers, industry stakeholders, academic peers, and students.

The post-doctoral positions are initially offered on a one-year contract basis, with potential for extension based on performance and project needs. Again, we are particularly and only interested in candidates who possess a deep and broad understanding of grid optimization.

Application Process:

Interested applicants are encouraged to submit their application by emailing Dr. Zongjie Wang at zongjie.wang@uconn.edu. Please include your CV, relevant publications in grid optimization, a cover letter highlighting your relevant experience and how you meet the qualifications listed above, and contact information for three references. We strongly encourage applications from individuals with a passion for renewable energy integration and grid optimization and resilience.

Closing Date:

Open until filled with review of applications to begin immediately.

Let’s embark on this transformative journey together to advance the state-of-the-art in power systems and contribute to a more resilient and sustainable energy future. Spread the word and join us in shaping the future of energy systems!