Graduate PhD Student Intern (Summer) – Mathematical Optimization

NREL•Golden, CO

About The Position

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.

Requirements

Minimum of a 3.0 cumulative grade point average.
Undergraduate: Must be enrolled as a full-time student in a bachelor’s degree program from an accredited institution.
Post Undergraduate: Earned a bachelor’s degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate: Must be enrolled as a full-time student in a master’s degree program from an accredited institution.
Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution.
Currently pursuing a PhD in applied mathematics, industrial engineering, chemical engineering, management science, operations research, or a related discipline
Demonstrated experience with algebraic modeling, including the use of modeling tools such as Pyomo, JuMP, GAMS, AMPL, CPLEX, Gurobi etc.
Demonstrated experience implementing algorithms with Python, Julia, or other major language

Nice To Haves

Experience with Pyomo and/or JuMP.
Experience with commercial and/or open-source optimization solvers (e.g., Gurobi, HiGHS, IPOPT).
Experience with developing custom math-programming algorithms tailored to specific problems.
Experience working with cross-disciplinary research teams
Experience with mpi-sppy and/or progressive hedging
Candidates should have demonstrated interest or experience in power systems planning and/or operations.
Experience with publishing
Experience with HPC workflows, bash script, linux etc.

Responsibilities

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

Benefits

Benefits include medical, dental, and vision insurance
403(b) Employee Savings Plan with employer match
sick leave (where required by law).
NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component.
Some positions may be eligible for relocation expense reimbursement.

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