Senior Plasma Modeling Scientist

Applied Materials; Santa Clara (CA); On-site; USD 138,000 - 190,000; Full time

Job summary

Applied Materials in Santa Clara, CA seeks a PhD-level scientist or engineer to develop and apply advanced modeling for plasma processing, including plasma etching, plasma-enhanced deposition, and atomic layer etching (ALE). This role blends physics-based and data-driven methods to understand and predict plasma-surface interactions.

The ideal candidate has hands-on experience with ab initio quantum chemistry, molecular dynamics, and kinetic Monte Carlo, and will develop ML models trained on

Qualifications

• PhD in Engineering (e.g., Chemical, Materials, Mechanical) or Science (e.g., Physics, Chemistry) or related field.
• Experience modeling plasma-surface or gas-surface interactions using ab initio, MD, and/or kinetic Monte Carlo methods.
• Strong background in machine learning for scientific computing or HPC environments.
• Experience integrating modeling results with experimental data.

Responsibilities

• Develop and apply models for plasma etching, deposition, and plasma-based surface modification processes.
• Combine physics-based and ML-driven approaches to improve understanding and predictions.
• Collaborate with experimental teams to guide process development and interpret results.
• Develop, validate, and maintain internal modeling tools and frameworks.
• Communicate results clearly to multidisciplinary teams including customers.

Skills

Modeling plasma-surface processes

ML for scientific computing

HPC data handling

Multidisciplinary communication

Education

PhD in Engineering or Science

Tools

Ab initio quantum chemistry

Molecular dynamics (MD)

Kinetic Monte Carlo (kMC)

Job description

Applied Materials in Santa Clara, CA seeks a PhD-level scientist or engineer to develop and apply advanced modeling for plasma processing, including plasma etching, plasma-enhanced deposition, and atomic layer etching (ALE). This role blends physics-based and data-driven methods to understand and predict plasma-surface interactions.

The ideal candidate has hands-on experience with ab initio quantum chemistry, molecular dynamics, and kinetic Monte Carlo, and will develop ML models trained on