We have an opening for a Postdoctoral Researcher in Operations Research to conduct research in the areas of stochastic, decentralized, and/or multi-level optimization, with specific application to critical infrastructure systems. You will be an integral part of a multi-disciplinary team of researchers, with skill sets ranging from computer and climate science to power and industrial engineering; projects are typically collaborative with partner academic institutions and other national labs. You will be developing advanced models of decision-making under uncertainty and adversarial contexts for critical infrastructure operations, planning, and resilience. You will join ongoing efforts in strategic capacity expansion planning and infrastructure interdiction but may also support other research initiatives sponsored by our U.S. Government partners. You will work with experienced LLNL scientists and engineers and contribute to new numerical methods and analysis tools that provide insights to inform near and long-term strategy and technology decisions. This position is in the Computational Engineering Division (CED), within the Engineering Directorate. The research will be conducted in conjunction with LLNL’s Cyber and Infrastructure Resilience (CIR) program. Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week. In this role, you will Develop and extend mathematical programming (e.g., mixed-integer programming, nonlinear programming, and mixed-integer nonlinear programming) formulations of core critical infrastructure operations and planning optimization models. Design and implement high-performance (parallel) solvers for stochastic, multi-level, and/or 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. 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 which requires U.S. citizenship. Ph.D. in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics, or closely related field. Fundamental knowledge of at least one open-source algebraic modeling language (e.g., Pyomo, JuMP) for mathematical optimization. Fundamental knowledge of at least one widely used mathematical optimization solver (e.g., HiGHS, Ipopt, Gurobi, CPLEX, and Xpress). Fundamental knowledge and experience developing software in a high-level language such as Python, Julia, and C++ (Python preferred). Experience developing specialized algorithms for mathematical optimization problems considering either adversarial (multi-level) behaviors, uncertain inputs, or at a large scale. Publication record in high-quality peer-reviewed journals and/or conferences. Proficient verbal and written communication skills to effectively collaborate in a team environment, present and explain technical information to technical as well as non-technical audiences, document work and write research papers. Qualifications We Desire Experience with high-performance computing systems, specifically parallel programming libraries such as MPI. Experience with the application of mathematical optimization to critical infrastructure systems, including electricity grid and natural gas networks. Experience processing and analyzing critical infrastructure information. Pay Range $122,028 - $143,328 Annually This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.
#LI-Hybrid Position Information This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date. Why Lawrence Livermore National Laboratory? Included in 2026 Best Places to Work by Glassdoor! Flexible Benefits Package 401(k) Relocation Assistance Education Reimbursement Program Flexible schedules (*depending on project needs) Our values - visit https://www.llnl.gov/inclusion/our-values Security Clearance This position requires a Department of Energy (DOE) Q-level clearance. If you are selected, we will initiate a Federal background investigation to d