Position Overview We are seeking a highly motivated PhD-level scientist or engineer to develop and apply advanced modeling capabilities for plasma processing applications, including plasma etching, plasma-enhanced deposition, and atomic layer etching (ALE). This role focuses on understanding, modeling, and predicting plasma-surface interaction processes using a combination of physics-based methods and data-driven approaches. The ideal candidate will have hands-on experience with atomistic and mesoscale modeling techniques such as ab initio quantum chemistry, molecular dynamics (MD), and kinetic Monte Carlo (kMC). In addition, the candidate will be expected to develop and deploy machine learning (ML) models trained on data generated from large-scale, multi-dimensional high-performance computing (HPC) simulations, complemented by experimental measurements. This position offers a unique opportunity to work at the intersection of first-principles modeling, large-scale simulation, and modern AI/ML methods, contributing directly to accelerated technology and product development in the fast-paced semiconductor equipment industry. Key Responsibilities

• Develop and apply advanced models for plasma etching, deposition, and plasma-based surface modification processes
• Combine physics-based and ML-driven approaches to improve process understanding and predictive capability
• Collaborate closely with experimental teams to guide process development and interpret new experimental results
• Contribute to the development, validation, and maintenance of internal software tools, modeling frameworks, and best practices
• Communicate modeling results clearly and effectively to multidisciplinary teams, including scientists, engineers, and major customers # # Applications will be reviewed on a rolling basis.

Please apply by October 30th, 2026.

Note:

This position may close early based on application volume or candidate selection. Minimum Qualifications

• Must have a PhD in Engineering (e.g., Chemical, Materials, Mechanical) or Science (e.g., Physics, Chemistry) or a related field
• Demonstrated experience modeling plasma-surface or gas-surface interaction processes using ab initio quantum chemistry, molecular dynamics, and/or kinetic Monte Carlo methods
• Strong background in machine learning, particularly in the context of scientific computing or HPC environments
• Experience working with large, complex simulation datasets and integrating modeling results with experimental data ## Qualifications ###

Education:

Doctorate Degree ### Skills ###

Certifications:

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Languages:

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Years of Experience:

4 - 7 Years ###

Work Experience:

## Additional Information ### ###

Shift:

10-Day 8-Hr (United States of America) ### ###

Travel:

Yes, 10% of the Time ### ###

Relocation Eligible:

Yes ###

Referral Payment Plan:

None Salary Range:

$138,000.00 - $190,000.00 The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable. For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement. Applied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.