Postdoctoral Researcher in Computational Kinetic Plasma Physics

What You Will DoWe 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 a high performance multidimensional electromagnetic kinetic plasma solver into a state-of-the-art multiphysics GPU production code.

The work will involve developing new numerical methods that leverage modern tensor decomposition techniques, time integration strategies, and adaptive mesh refinement to enable full system scale kinetic modeling of extreme-scale DoE applications.

A strong background in plasma physics with emphasis on kinetic models and high performance computing (HPC) 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 NeedMinimum Job Requirements:Education/Experience: A Ph.D. in Plasma Physics, Astrophysics, 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 effectively networking with peers.

Expertise in HPC.

Proficiency in C/C++.

Desired Qualifications:

Experience in developing and implementing numerical methods for solving PDEs (e.g., Eulerian, semi-Lagrangian, PIC).

Strong experience programming with GPU.

Experience working on large complex scientific software.

Experience with Kokkos.

Experience with Parthenon framework:

Experience with modern low-rank tensor methods (e.g., tensor trains)