Postdoctoral Scholar - Plasma Simulation and Machine Learning.

Responsibility:

-Develop efficient first-principle algorithms for kinetic plasma simulation of particle accelerators and fusion devices.
-Develop physics-informed machine learning algorithms as surrogate simulators for particle accelerators and fusion devices.
-Develop high-performance machine learning packages that can be integrated with existing particle-in-cell or fluid-based codes.
-Work in a multidisciplinary team environment including mathematicians, computer scientists, and domain scientists.
-Write peer-reviewed journal articles and attend international/domestic conferences.

Requirement:

-PhD (by the time of the appointment) in Mathematics, Computer Science, Computational Science, Physics, Engineering, or equivalent.
-Expertise in computational electromagnetics or plasma simulation with at least one of the following experiences: particle-in-cell, boundary element method,time-domain simulation, and fast analytical or algebraic algorithms.
-Knowledge of machine learning algorithms and fast numerical linear algebra is a plus.
-Proficiency in a high-performance programming language including C/C++/Fortran and MPI.
-US citizenship or permanent residency is NOT required.