Computational Associate Research Scientist in the Area of Low-Temperature Low-Pressure Processing Plasma

Tips: Provide a summary of the role, what success in the position looks like, and how this role fits into the organization overall.ResponsibilitiesThe Princeton Plasma Physics Laboratory (PPPL) is seeking to appoint a Associate Computational Scientist to contribute to the advancement of modeling capabilities and physics research pertaining to low-temperature plasmas and associated technologies. The primary responsibility of this position involves conducting and facilitating computational modeling of authentic low-temperature plasma devices, particularly those operating at low pressure, for the purposes of scientific discovery and engineering design. The successful candidate will achieve this objective through the application of high-performance computing (HPC) best practices, advanced mathematical research into novel algorithms, and the utilization of machine learning techniques for code acceleration and the development of reduced-order "surrogate" models.This will require working with and maintaining the LTP-PIC software, a particle-in-cell (PIC) software package developed at PPPL for these purposes. The candidate should have strong familiarity with compiler level languages, accelerated computing (preferably with OpenMP or OpenACC) and distributed computing (MPI). A thorough understanding of the particle-in-cell algorithm, its inherent limitations, and potential avenues for performance enhancement is also required. Furthermore, the candidate should demonstrate substantial practical knowledge of low-pressure magnetron, capacitively and inductively coupled discharges employed in plasma processing, coupled with a proven track record of kinetic modeling of such discharges.QualificationsEducation and Experience: Ph.D. in Physics, Engineering or a related field with core training in low-temperature plasma physics and high-performance computing.Minimum 3 years of professional experience in an academic, scientific, or R&D environment is preferred.A proven track record of publishing original results in peer-reviewed scientific journals.A proven track record of developing high-performance codes.Demonstrated collaborative experience within academia and with industry.