Postdoctoral Researcher in Dynamic Systems, Optimization, Control, and Energy Networks

About the role

The selected candidate will work closely with mentors and other collaborators to develop novel algorithms for surrogate modeling, inference, parameter estimation, optimization, optimal control, and/or economic analysis of energy networks focusing on electric power and natural gas transmission and distribution. The work will involve developing new numerical methods that use spectral approximation, interior point optimization, and numerical linear algebra, potentially using high-performance computing on novel architectures and agentic artificial intelligence systems.

Responsibilities

• Develop novel algorithms for surrogate modeling, inference, parameter estimation, optimization, optimal control, and/or economic analysis of energy networks focusing on electric power and natural gas transmission and distribution.
• Collaborate with mentors and other collaborators to advance research in dynamical systems, control theory, optimization, and network science.
• Use spectral approximation, interior point optimization, and numerical linear algebra to develop new numerical methods for optimization in function space.
• Implement and test these methods on high-performance computing platforms and agentic artificial intelligence systems.
• Contribute to publications and presentations in scientific conferences and journals.

Requirements

• A Ph.D. in Applied Mathematics, Engineering, Computer Science, Computational Science, or a closely related field completed within the past five years or soon to be completed.
• Demonstrated ability to publish in scientific journals, and to communicate effectively, both written and orally.
• Ability to collaborate effectively in a team environment and develop solutions for complex problems while networking with peers.
• Expertise in dynamical systems, control theory, optimization, and network science.
• Proficiency in one or more of MATLAB, Python, Julia, Rust, and/or C/C++.

Qualifications

• Experience in developing and implementing numerical methods for optimization in function space.
• Experience in scientific computing.
• Experience with software development and version control.
• Experience with quantitative economics.

Skills

• Strong background in optimization and control with emphasis on numerical methods and algorithms.
• Demonstrated ability to develop and test novel computational methods to address scientific and technical issues.

Benefits

Competitive salaries are based on the date the PhD degree requirements were completed or the degree was awarded. Starting salary for a new graduate is currently $97,000.

Pay

Starting salary for a new graduate is currently $97,000.

Schedule

The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.