Location: Los Alamos, NM
Cap-Exempt H-1B Position — No lottery required
**What You Will Do** We are seeking qualified candidates to join the Theoretical Division (T-Division) at Los Alamos National Laboratory. T-Division offers a dynamic and intellectually stimulating environment that promotes interdisciplinary collaboration in support of the Laboratory's strategic basic research and national security missions. Within T-Division, the Applied Mathematics and Plasma Physics Group (T-5) conducts cutting-edge research in areas such as novel algorithms, numerical methods, and theoretical modeling. Applications span a wide range of fields, including fusion and high energy density science, space plasma physics, astrophysics, numerical analysis, machine learning, computational imaging, optimization, artificial intelligence, environmental science, and the modeling of critical infrastructure systems such as gas pipelines and electrical grids. 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. A strong background in optimization and control with emphasis on numerical methods and algorithms is required, and a demonstrated ability to develop and test novel computational methods to address scientific and technical issues is preferred. The initial appointment is for two years, with the possibility of a third-year extension contingent on performance and available funding. **What You Need** **Minimum Job Requirements:** **Education/Experience**: A Ph.D. in Applied Mathematics, Engineering, Computer Science, Computational Science, or a closely