Computational Scientist - 2D Materials & Plasma Processing

Princeton Plasma Physics Laboratory; Merrifield (VA); Hybrid; USD 111,000 - 178,000; Full time

Job summary

Princeton Plasma Physics Laboratory seeks a Computational Scientist to advance modeling and physics research in coupling low-temperature plasmas with two-dimensional materials and related technologies.

The role emphasizes DFT modeling with ab initio molecular dynamics, development of machine learning potentials for MD acceleration, and strong dissemination of results through publications and international conferences. Collaboration across academia and industry is essential.

Qualifications

• Ph.D. in Physics, Engineering or 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.
• A proven track record of publishing original results in peer-reviewed scientific journals.
• Demonstrated collaborative experience within academia and with industry.
• Strong ability to connect atomistic results to experimentally relevant materials properties.

Responsibilities

• Apply ab initio molecular dynamics to low-temperature plasmas for processing of 2D materials.
• Define and deliver on AI projects for low-temperature plasmas.
• Proposal ideation and preparation for future research funding.
• Model plasma processing for industry partners; publish results at conferences.

Skills

DFT/MD modeling

2D materials

ab initio MD

ML potentials

electronic structure

multidisciplinary teamwork

Education

Ph.D. in Physics/Engineering

Tools

VASP

CP2K

Gaussian

Quantum ESPRESSO

LAMMPS

Job description

Princeton Plasma Physics Laboratory seeks a Computational Scientist to advance modeling and physics research in coupling low-temperature plasmas with two-dimensional materials and related technologies.

The role emphasizes DFT modeling with ab initio molecular dynamics, development of machine learning potentials for MD acceleration, and strong dissemination of results through publications and international conferences. Collaboration across academia and industry is essential.