This role pays more than
61%
of similar roles. Most pay
$104,000–$212,500
— the shaded band above.
At the midpoint, this role pays about
$164k
versus about
$158k
for comparable roles.
Based on 240 similar postings.
Employer
About Applied Materials
Applied Materials is the world''s largest supplier of equipment, services, and software for the semiconductor and display industries, enabling the production of chips and advanced displays. Industry: Semiconductor Equipment
Applied Materials currently has
134 open roles
on FindRole.
Listed pay typically runs
$132,750–$182,500
across 134 roles with salary data.
New College Grad - Physicist/Scientist III - PhD (2027 Summer Cohort) is a role focused on developing and applying advanced modeling capabilities for plasma processing applications, including plasma etching, deposition, and atomic layer etching. The scientist will work at the intersection of first-principles modeling, large-scale simulation, and modern AI methods to understand and predict plasma–surface interaction processes. Day-to-day responsibilities include building physics-based and machine learning models, collaborating with experimental teams to guide process development, and maintaining internal software tools and modeling frameworks. The role requires expertise in ab initio quantum chemistry, molecular dynamics, and kinetic Monte Carlo techniques, alongside experience with high-performance computing environments and large, complex simulation datasets. This position addresses critical technical challenges within the semiconductor equipment industry by improving predictive capabilities for surface modification processes through integrated data-driven and physics-based approaches.
Integrate modeling results with experimental measurements to guide product development.
Develop, validate, and maintain internal software tools and modeling frameworks.
Communicate complex modeling results to multidisciplinary teams and major customers.
What we're looking for
Must have a PhD in Engineering (e.g., Chemical, Materials, Mechanical), 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 within the context of scientific computing or HPC environments.
Experience working with large, complex simulation datasets and integrating modeling results with experimental data.