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Physics World · 1 month ago

Operations Research Engineer

Livermore, CA

Full-time

Hybrid

Mid, Senior Level

$117K/yr - $178K/yr

Lawrence Livermore National Laboratory (LLNL) is seeking an Operations Research Engineer to contribute to energy systems simulation and management. The role involves supporting optimization models for energy networks and collaborating with multi-disciplinary teams to address technical challenges.

Publishing

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Perform defined work in supporting of development of optimization models for energy networks, including formulation, implementation, solution, analysis and communication

Support the construction of coherent datasets to feed long-term optimal capacity expansion models of energy systems, including technology costs, geographical characteristics (solar irradiance, wind speeds, wildfire propensity, etc.), regulatory frameworks, human factors, climate and extreme weather events, among others

Contribute to cross-functional and multi-disciplinary teams to solve technical problems

Provide solutions to limited-complex problems related to modeling and simulation, or other technical analyses

Contribute information, fulfillment and findings from studies

Perform other duties as assigned

Perform defined work of moderate complexity aiding with contribution to the development of analytical frameworks providing insight to customers on various challenges

Work under limited direction to design and implement numerical methods, techniques and evaluation criteria while exercising independent judgment

Explore a variety of approaches within generally established methods. Make recommends improvements/processes as appropriate

Contribute to the overall fulfillment of project and organizational goals

Qualification

Energy systems simulationMathematical optimizationScientific programming languagesAlgebraic modeling languagesData processingVerbal communicationWritten communicationTeam collaboration

Required

Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship

Master's degree in physical science, engineering, operations research, economics or a related field, or equivalent combination of education and related experience

Ability to use and apply of standard technical and/or business principles, theories, concepts, and techniques

Demonstrated competence in one or more scientific programming languages, such as Python, Julia, C++, R, Matlab, or Rust

Demonstrated ability to implement mathematical optimization problems using at least one algebraic modeling language, such as Pyomo (preferred), Gurobipy, JuMP, AMPL, GAMS, among others, and use standard solver packages-such as Gurobi, CBC, HiGHS, or Ipopt, among others-to solve them

Proficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information

Demonstrated ability to process data from multiple sources into coherent datasets

Familiarity with decomposition techniques in stochastic optimization, such as Benders, ADMM, Progressive Hedging, SDDP

Ability to effectively manage concurrent technical tasks with competing priorities and meet deadlines that are important to project success

Preferred

PhD in physical science, engineering, operations research, economics or a related field, or equivalent combination of education and related experience

Demonstrated ability to design specialized algorithmic approaches for challenging mathematical optimization problems