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!
