Computational Optimization Postdoctoral Researcher

We have an immediate opening for a Computational Optimizer 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. The ability to conduct fluid engagement with domain experts and end-users to characterize analyze and communicate inputs and solutions is critical in this role. Development of advanced mathematical optimization models (e.g. MIP formulations) and scalable (e.g. via decomposition) solvers will be a primary technical focus. This position is in the Center for Applied Scientific Computing (CASC) which resides within the Computing Directorate at LLNL. The research will be conducted in conjunction with LLNLs Cyber and Infrastructure Resilience (CIR) program.

In this role you will

• Develop and extend mathematical programming (e.g. MIP NLP and MINLP) 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.
• 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.

Qualifications :

• 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.
• Working knowledge of at least one algebraic modeling language (e.g. Pyomo JuMP AMPL and GAMS) for mathematical optimization.
• Working knowledge of at least one widely used mathematical optimization solver (e.g. Gurobi CPLEX and Express).
• Experience developing software in a high-level language such as Python Julia and C (Python preferred). 
• Experience developing advanced optimization solvers considering either 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 technical as well as non-technical audiences document work and write research papers.

Desired qualifications (optional)

• 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 geospatial information including climate and weather data.

Additional Information :

#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 2025 Best Places to Work by Glassdoor!
• Flexible 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.  If you are selected we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also all L or Q cleared employees are subject to random drug testing.  Q-level clearance requires U.S. citizenship. 

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  Remote Work :

  No

  
  

  Employment Type :

  Full-time