Supported by the Alfred P. Sloan Foundation, the Energy Data Analytics Ph.D. Student Fellows program at Duke University readies emerging scholars to apply cutting-edge data science techniques to energy challenges.
The recent growth of energy-related data and evolution of data science techniques have created promising new opportunities for solving energy challenges. Capitalizing on these will require scholars with training in both data science and energy application domains. Yet traditional graduate education is limited in its ability to provide such dual expertise.
Established in 2018, the Energy Data Analytics Ph.D. Student Fellows program at Duke University prepares cohorts of next-generation scholars to deftly wield data in pursuit of accessible, affordable, reliable, and clean energy systems.
Each Ph.D. Student Fellow in the program conducts a related research project, working with faculty from multiple disciplines and receiving funding for 3 months of summer support and $1,500 in research funds for computation and professional development. The fellows take part in regular mentorship and training workshops to improve their understanding of energy systems and data science tools as well as to enhance their skills at collaborating and communicating across disciplines.
The program is open to doctoral students at Duke University, North Carolina A&T State University, North Carolina State University, University of North Carolina at Chapel Hill, University of North Carolina at Charlotte, and University of North Carolina at Greensboro.
The Energy Data Ph.D. Student Fellows Program is currently accepting applications for its 2023 cohort. Learn more below, and submit the application form to Trey Gowdy (trey.gowdy@duke.edu) as a PDF by 5 p.m. ET on Dec. 9, 2022. Ask your faculty project advisors to submit their nomination letters by the same date.
- Any Duke University, NC A&T State University, NC State University, UNC Chapel Hill, UNC Charlotte, or UNC Greensboro doctoral student currently enrolled full-time in their degree program is welcome to apply. Note: As Duke University is the host institution for this grant, approximately half of the Fellowships will go to Duke students each year.
- The student must be working with (or proposing to work with) two faculty members representing interdisciplinary expertise across both an energy application domain (e.g., energy technologies, systems, markets, and policies) and a data science field (e.g., statistics, machine learning, and other computational methods). These faculty members can both be from the student’s home university or one may be from one of the other eligible universities listed above.
- Doctoral student must show evidence of genuine interest in research on energy data analytics topics that incorporate data science methodologies/tools. It is preferable if the proposed work plays a role in their larger dissertation objectives.
- Applicants must be making successful academic progress in their home department.
- Three months of 100% funding support for summer 2023 covering student stipend and fringe benefits, and 50% support for tuition remission – up to a total of $11,117 (based on Duke University amounts). Details vary by home university. Note: No home-institution overhead will be compensated.
- Funding for research supporting data collection, software tools, equipment, conference participation, publication, or other research-related needs up to $1,500 will be available to Fellows.
- Mentorship and training from interdisciplinary energy and data science scholars.
- Fellows’ work will be spotlighted on the Energy Data Analytics Ph.D. Student Fellows program webpage and at an Energy Data Analytics Symposium in 2023.