Physics AI Scientist III

Applied Materials•Santa Clara, CA

2d•$161,000 - $221,000

About The Position

Develop next-generation AI models for semiconductor engineering by combining scientific domain knowledge with modern machine learning. Build physics-aware surrogate models, foundation models, and optimization workflows that accelerate simulation and engineering design. Applied Materials is a global leader in materials science and engineering solutions underlying semiconductor chips and advanced displays. Its equipment and services support the advancement of AI and the commercialization of next-generation semiconductor chips.

Requirements

Experience applying machine learning to real-world scientific or engineering problems.
Strong background in scientific machine learning and numerical simulation.
Experience with surrogate modeling, PINNs, operator learning (e.g., FNO), or foundation models.
Proficiency in Python and PyTorch.
Experience with HPC, distributed training, large-scale scientific datasets, or scalable ML workflows.

Nice To Haves

Ph.D. in Mechanical Engineering, Chemical Engineering, Materials Science, Physics, Applied Mathematics, Computer Science, or a related field.

Responsibilities

Develop Scientific AI models that bridge scientific computing, physics-based simulation, and machine learning for physics- and chemistry-based engineering problems.
Design and train surrogate models, operator-learning models, and foundation models for scientific simulations.
Collaborate with domain experts to formulate AI solutions for complex engineering challenges.
Develop scalable data-generation, training, validation, and deployment workflows for Scientific AI models.
Publish technical innovations and drive adoption of Scientific AI across engineering applications.