Modeling Engineer: Plasma Process and Machine Learning
About The Position
Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. What We Offer Salary: $161,000.00 - $221,000.00 Location: Santa Clara,CA You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more. At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits . 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.
Requirements
- PhD in Engineering (e.g., Chemical, Materials, Mechanical) or Science (e.g., Physics, Chemistry); exceptional MS candidates with relevant experience will be considered
- 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
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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
Number of Employees
11-50 employees
