Computational Optimization Postdoctoral Researcher

Computational Optimization Postdoctoral Researcher

Physics World invites applications for the role of Computational Optimization Postdoctoral Researcher at the Lawrence Livermore National Laboratory (LLNL). This position is immediately available and offers a postdoctoral appointment with the potential to extend up to three years for those who have earned a PhD at the time of hire.

Pay Range: $138,480 Annually (lowest to highest salary we in good faith believe we would pay for this role at the time of posting; pay will not be below any applicable local minimum wage).

Job Description: Conduct research in stochastic, decentralized, and multi‑level optimization with specific application to critical infrastructure systems. Work in a multidisciplinary team within the Center for Applied Scientific Computing (CASC) and collaborate with LLNL’s Cyber and Infrastructure Resilience (CIR) program.

• Develop and extend mathematical programming (e.g., MIP, NLP, MINLP) formulations for core critical infrastructure operations and planning models.
• Design and implement high‑performance (parallel) solvers for stochastic, multi‑level, and decentralized optimization models of critical infrastructure.
• Analyze and mitigate performance bottlenecks in parallel solver implementations.
• Publish research results in external peer‑reviewed scientific journals and participate in conferences and workshops.
• Present formal and informal overviews of research progress at group meetings.
• Contribute to grant proposals and collaborate with others in a multidisciplinary team environment to accomplish research goals.
• Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
• Perform other duties as assigned.

• Ability to secure and maintain a U.S. DOE Q‑level security clearance (requires U.S. citizenship).
• Ph.D. in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics, or a closely related field.
• Working knowledge of at least one algebraic modeling language (e.g., Pyomo, JuMP, AMPL, GAMS).
• Working knowledge of at least one widely used mathematical optimization solver (e.g., Gurobi, CPLEX, Express).
• Experience developing software in a high‑level language such as Python, Julia, and C++ (Python preferred).
• Experience developing advanced optimization solvers involving adversarial (multi‑level) behaviors, uncertain inputs, or decentralized contexts.
• Publication record in high‑quality peer‑reviewed journals and/or conferences.
• Analytical and problem‑solving skills necessary to craft creative solutions to independently solve complex problems.
• Proficient verbal and written communication skills to effectively collaborate in a team environment, present and explain technical information to both technical and non‑technical audiences, document work and write research papers.

• Experience with high‑performance computing systems, specifically parallel programming libraries such as MPI.
• Experience applying mathematical optimization to critical infrastructure systems (e.g., electricity grid, natural gas networks).
• Experience processing and analyzing geospatial information, including climate and weather data.

• Included in 2025 Best Places to Work by Glassdoor!
• Flexibile Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (depending on project needs)
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This position requires a Department of Energy (DOE) Q‑level clearance. Eligible applicants will undergo a federal background investigation. All L or Q cleared employees are subject to random drug testing. Q‑level clearance requires U.S. citizenship.

External applicant(s) selected for this position must pass a post‑offer, pre‑employment drug test, including testing for marijuana as Federal Law applies to us as a Federal Contractor.

We are an equal opportunity employer committed to providing a work environment free of discrimination and harassment. All qualified applicants will receive…