Graduate PhD Student Intern (Summer) –… at National… · Golden

Summary: National Laboratory of the Rockies (NLR) is the nation's primary laboratory for energy systems research and development. They are seeking a Graduate PhD Student Intern to work on large-scale power systems planning, developing optimization algorithms and collaborating with researchers to enhance the reliability and security of bulk electric systems. 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 Required Qualifications: - 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 Preferred Qualifications: - 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 Required Skills: Mathematical Optimization, High-Performance Computing, Algebraic Modeling Important Skills: Python, Pyomo, Gurobi Nice-to-Have Skills: Cross-disciplinary Research, Collaboration, Technical Writing Benefits: Medical, dental, and vision insurance, 403(b) Employee Savings Plan with employer match, Sick leave (where required by law), Performance-, merit-, and achievement- based awards that include a monetary component, Relocation expense reimbursement