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

Overview

The 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.

The candidate should be familiar with machine-learning principles for science, including generative A.I. and surrogate models, especially of convolutional and recurrent neural networks. Familiarity with Python, NumPy and PyTorch will be essential for this position.

The computational tools developed will be instrumental in studies of magnetron, capacitively-coupled plasmas and partially magnetized plasma sources, as well as the fundamental understanding of anomalous transport and plasma turbulence within these devices. The software will also be disseminated to the broader academic and industrial communities, necessitating strong interpersonal and communication skills to cultivate these relationships.

This position is part of PPPL's prestigious Strategic Science Initiative (SSI) Fellowship Program, which provides exceptional early-career researchers with the opportunity to lead innovative research and help advance new scientific directions at the Laboratory. As an SSI Fellow, the successful candidate will serve as an Associate Research Scientist and contribute to PPPL's research in applied materials and electromanufacturing, with a focus on advancing computational modeling, high-performance computing, and machine learning for low-temperature plasma science and technology.

Responsibilities

Core Duties:

• The candidate will be responsible for ongoing development and maintenance of the LTP-PIC software, as well as assisting users from academia and industry (50%).
• Defining and delivering on A.I. projects for low-temperature plasmas (20%).
• Modeling low-pressure discharges for industry partners (20%).
• Publishing scientific results and dissemination at major international conferences (10%).

Qualifications

Education 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.

Working Conditions:

• Regular office hours.
• The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.

Standard Weekly Hours

40.00

Eligible for Overtime

No

Benefits Eligible

Yes

Probationary Period

180 days

Essential Services Personnel (see policy for detail)

No

Physical Capacity Exam Required

No

Valid Driver's License Required

No

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Salary Range

$93,500 to $149,300