Sort by
Refine Your Search
-
, numerical optimization, numerical partial differential equations, and parallel computing. The Researcher will join a project developing parallel high-order meshing algorithms from medical images and parallel
-
, including hybrid simulations coupling machine learning with numerical methods, multiscale discretization, nonlocal closure modeling, structure preservation, multilevel and multifidelity machine learning
-
, applied math, computational math, or a related field at the time of the appointment. Experience in computational plasma physics, numerical methods, and HPC. Ability to function and thrive in a collaborative
-
experience in intensive and parallel computing (Fortran, C, C++, Python). Applicants with a previous background in at least one of the following techniques, • Quantum Monte Carlo (either DQMC, PQMC, DCA, SSE
-
#, FORTRAN, Perl, Python) as well as parallel computing; Ability to work effectively in a team environment with a multidisciplinary group of scientists Ability to conduct research with limited supervision Good
-
, as well as numerical methods for partial differential equations, especially finite element methods, both theory and implementation. A successful candidate will work in the topics of interests, which
-
, components and systems. Knowledge of analyses of components and energy conversion systems. Knowledge of computational techniques and numerical methods. Knowledge of computer simulation and data analysis
-
and energy conversion systems. Knowledge of computational techniques and numerical methods. Knowledge of computer simulation and data analysis. Knowledge of C/C++ language and parallel programming with
-
relevant numerical methods to dramatically reduce time to a feasible solution, parallelization of computations/high-performance computing, and other emerging and novel techniques to improve the efficiency