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Los Alamos National Laboratory · 1 day ago

Postdoctoral Researcher in Computational Kinetic Theory

Los Alamos, NM

Full-time

Onsite

New Grad, Entry Level

$94K/yr - $94K/yr

Los Alamos National Laboratory is a multidisciplinary research institution engaged in strategic science on behalf of national security. They are seeking a Postdoctoral Researcher in Computational Kinetic Theory to work on advancing a novel formulation of kinetic equations across various domains, developing new numerical methods for solving these equations.

Security

Growth Opportunities

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Work closely with mentors and other collaborators to advance a novel formulation of kinetic equations-referred to as conditional kinetics across various domains, including plasmas, neutrons, photons, phonons, and gases

Develop new numerical methods for solving kinetic equations

Qualification

Numerical methods for PDEsPlasma physicsAstrophysicsProgramming languagesApplied mathematicsParallel computingHigh performance computingMultiscale methodsTeam collaborationEffective communication

Required

A Ph.D. in Applied Mathematics, Plasma Physics, Astrophysics, Engineering, 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 analysis, development, implementation, and testing of numerical methods for solving hyperbolic and/or parabolic PDEs

Proficiency in several of the following programming languages: C/C++, Python, and Julia

Preferred

Experience in curvilinear geometry as well as applications of symplectic geometry

Experience in developing structure preserving discretization schemes

Experience in low-rank tensor decomposition methods and their applications to solving high dimensional PDEs

Experience in using high performance scientific software libraries (e.g., petsc, trillinos, MFEM, sundials)

Experience in parallel computing (MPI, OpenMP, Cuda, Kokkos, Raja)

Experience in linear and nonlinear solvers (e.g., Krylov, Newton, preconditioning, multigrid, Anderson acceleration)

Experience in developing multiscale and multiphysics methods for kinetic equations (e.g., micromacro decomposition, high-order low-order (HOLO) solvers, physics domain decomposition, fast-slow decomposition etc.)

Experience with developing asymptotic reduced order models through e.g., Hilbert and Chapman-Enskog expansion