Graduate PhD Student Intern - Mathematical Optimization 🎓

The AI, Learning and Intelligent Systems (ALIS) Group in the NLR Computational Science Center has an opening for a graduate student researcher in Mathematical Optimization for large-scale power systems planning. They will deploy developed optimization algorithms on DOE high-performance computing systems. The researcher will develop mathematically sound approaches for transmission and capacity expansion as applied to the bulk electricity systems to enhance economics, reliability, resilience, and security of bulk electric systems.

Responsibilities include:

• Develop and implement mathematically sound approaches for transmission and capacity expansion using distributed optimization methods on NLR’s HPC

• Collaborate with NLR researchers to assess tradeoffs between model detail and computational time

• Process and visualize results to inform algorithmic design

• Author, present and assist in the preparation of technical papers, reports and conference proceedings on topics related to power systems planning