Associate Research Physicist – Radio Frequency (RF) Wave Physics
The Princeton Plasma Physics Laboratory (PPPL) is seeking a highly motivated scientist with a previous experience in Plasma Physics, particularly with Radio Frequency (RF) Wave Physics combined with a computational experience. This position will be responsible for expanding the various physics and solver components in the Petra-M FEM platform.
This position will also be actively involved with the U.S. Department of Energy’s (US DOE) RF SciDAC project and with Artificial Intelligence (AI)/Machine Learning (ML) engineers and Advanced Science Computing Research (ASCR) scientists at other leading US DOE supported labs like Brookhaven National Lab (BNL) and Lawrence Livermore National Lab (LLNL).
The Princeton Plasma Physics Laboratory is a world-class fusion energy research laboratory managed by Princeton University for the U.S. Department of Energy’s Office of Science. PPPL is dedicated to developing the scientific and technological knowledge base for fusion energy. The Laboratory advances the fields of fusion energy and plasma physics research to develop the scientific understanding and key innovations needed to realize fusion as an energy source for the world.
The RF wave heating, a major tool to heat plasmas and to maintain fusion reactions, injects high frequency RF waves using geometrically complicated antenna closely located to the plasma, and waves are absorbed by plasma through linear and non-linear processes. Accurate modeling is crucial to extend our present-day knowledge from fusion plasma experiments to up-coming fusion reactors such as ITER. Computing the RF wave field in hot plasma requires solving the large scale Vlasov-Maxwell type equation defined in 3D space, requiring modern hardware and computing algorithms.
This position will include two main areas of topical research:
Development, maintenance, and application of the RF wave simulation model based on finite elements
Accelerating the radiofrequency (RF) wave field solver with artificial intelligence/machine learning (AI/ML) technology.
Ph.D. in plasma physics, applied math, or a closely related discipline required
Knowledge of radio-frequency wave physics in plasmas.
Experience in computational physics code development,
Fluency in the scientific programing languages such as C++, FORTRAN and Python
Collaborative experience with code authors and other software engineers.
Familiarity with AI/ML libraries such as PyTORCH.
Linear solvers and pre-conditioners.