Computational Optimization Postdoctoral Researcher

Company Description

Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are dedicated to fostering a culture that values individuals, talents, partnerships, ideas, experiences, and different perspectives, recognizing their importance to the continued success of the Laboratory’s mission.

Pay Range

$138,480 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.

Job Description

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 LLNL’s 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 processin