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 :

Desired qualifications (optional)

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

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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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External applicant(s) selected for this position must pass a post-offer pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

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Remote Work : No

Employment Type : Full-time

Key Skills

Intelligence Community Experience,Python,Spss,Microsoft Word,R,Regression Analysis,Windows,Stata,Microsoft Powerpoint,Research Experience,Data Modeling,Writing Skills

Experience : years

Vacancy : 1