The Sustainable Power and Energy Lab (SPEL) at the Department of Electrical and Computer Engineering of the University of Connecticut invites applications for at least two Postdoctoral Research Associate positions and two PhDs starting in early August 2024. These positions are central to the technical leadership and advancement of the Wind Impact Study for Power Resilience (WISPR) project, recently funded by the Department of Energy. The selected candidates will be working on developing advanced risk assessment models and optimization methodologies for enhancing grid resilience, specifically through improved vegetation management and integration of climate projections.
Selected candidates will be responsible for:
- Managing the WISPR project to ensure successful delivery and execution of specified tasks and milestones.
- Collaborating closely with industry partners, national laboratories, and software vendors to co-lead the project towards achieving its goals.
- Utilizing asset information, historical outage data, and climate projections to develop a dynamic risk assessment model that identifies patterns between vegetation management and power outages.
- Integrating advanced optimization techniques and intelligent management strategies into the risk assessment model to enhance grid resilience and reduce electricity costs.
- Performing comprehensive cost-benefit analyses using advanced econometric models to optimize resilience improvement strategies.
- Assisting in writing and publishing quarterly progress reports and contributing to top-tier journal publications in the field.
- Managing and contributing to the project’s open-source codebase on GitHub.
- Engaging in collaborative research activities, promoting innovation and knowledge exchange within and beyond the project team.
- Contributing 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) in Electrical Engineering, or a closely related field, with a strong and specific focus on grid resilience, grid optimization, vegetation management, and risk assessment modeling.
- Expertise in programming languages such as Python, R, or MATLAB, and optimization software. Experience with Julia will be considered an additional credit.
- Solid experience with GitHub.
- 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 optimization and grid operation is an additional credit.
- Excellent communication skills, with the ability to articulate complex technical concepts to a broad range of audiences, including DOE program managers, industry stakeholders, academic peers, and students.
This position is initially offered on a one-year contract basis, with potential for extension based on performance and project needs. We are particularly interested in candidates who possess a deep and broad understanding of grid resilience and optimization, and vegetation management.
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 resilience and 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 resilience.
Let’s embark on this 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!
Closing Date:
Open until filled with review of applications to begin immediately.