Design, analysis and application of distributed optimization and control algorithms with applications to next-generation energy systems. Candidates should possess technical expertise in one or more of the following topics: convex and nonconvex optimization, nonlinear programming, distributed solvers for convex and nonconvex programs, and convex relaxation/approximations of nonconvex nonlinear programs. Application domains for the aforementioned theoretical toolboxes include, but are not limited to: real-time control of smart grids, optimal power flow, stochastic optimal power flow, multi-energy systems.
Required Education, Experience, and Skills
Must be enrolled as a full-time student in a degree granting program, or graduated in the past 12 months from an accredited institution. Internship period cannot exceed 12 months past graduation. Minimum of a 3.0 cumulative grade point average. Please Note: Before interview selection, you will need to provide unofficial transcripts to verify GPA and full time enrollment.
- Term Intern summer 2018
- Company NREL