Physicist/Scientist Machine Learning

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.

Requirements

• MS or PhD in Engineering (e.g., Chemical, Electrical, Mechanical, Aerospace, Nuclear, Materials), Science (e.g., Physics, Chemistry), or Computer Science
• Significant experience developing machine learning or deep learning models using data from multi‐dimensional numerical simulations (e.g., PDE‐based solvers, particle‐based simulations, multiphysics models)
• Strong background in Python‐based scientific computing and ML workflows
• Demonstrated experience with PyTorch or equivalent deep learning frameworks
• Solid understanding of: Data preprocessing and feature engineering for large, high‐dimensional datasets, Model training, validation, and performance evaluation, Numerical methods and/or physics‐based modeling concepts
• Experience with NVIDIA Physics NeMo, NVIDIA Modulus, or related physics‐informed or simulation‐driven ML libraries
• Familiarity with GPU‐accelerated computing, CUDA‐aware workflows, and HPC environments
• Exposure to physics‐informed machine learning (PIML), surrogate modeling, reduced‐order modeling, or operator learning
• Publications or demonstrated research contributions in ML for physical systems or related fields

Benefits

• Generous Paid Time Off
• 401k Matching
• Retirement Plan