AI Materials Research Engineer

About the role

Applied Materials is seeking an AI Materials Research Engineer to accelerate semiconductor materials discovery using scientific AI, computational materials science, and machine learning. The role blends deep materials expertise with AI/ML, simulation, and data‑driven modeling to create next‑generation materials and process innovations.

Key responsibilities

• Develop AI/ML models for property prediction, materials screening, optimization, process‑performance modeling, and generative materials design.
• Apply computational methods such: density functional theory, molecular dynamics, kinetic Monte Carlo, and phase‑field simulations.
• Build AI surrogate models to speed up simulation‑driven research and create informatics pipelines that integrate experimental data, characterization results, simulation outputs, and scientific literature.
• Design AI copilots and agentic workflows for literature review, hypothesis generation, experiment planning, and simulation orchestration.
• Collaborate with materials scientists, process engineers, and AI teams to deliver scientific AI solutions.

Required profile

• MS or PhD in Materials Science, Computational Materials Science, Physics, Chemical Engineering, or a related discipline.
• 2–5 years of experience in computational materials science, materials informatics, scientific machine learning, or AI for scientific applications.
• Strong Python programming skills and experience with ML frameworks such as PyTorch, TensorFlow, or Scikit‑Learn.
• Hands‑on experience with at least one computational method (DFT, MD, kMC, or phase‑field modeling).
• Solid understanding of crystal structures, thermodynamics, kinetics, defect physics, and semiconductor materials.

Required skills

• Python
• PyTorch
• TensorFlow
• Scikit‑Learn
• Density Functional Theory (DFT)
• Molecular Dynamics (MD)
• Kinetic Monte Carlo (kMC)
• Phase‑Field Modeling
• VASP, Quantum Espresso, CP2K, LAMMPS, GROMACS
• Materials Project, OQMD, NOMAD databases
• Graph Neural Networks
• Materials Foundation Models
• Physics‑Informed Machine Learning
• Generative AI for materials design
• Cloud and HPC environments for large‑scale model training and simulations

What we offer

• Salary range $170,000 – $234,000 per year.
• Supportive work culture that encourages learning, development, and career growth.
• Comprehensive health, wellbeing, and benefits programs, including bonus and stock award opportunities.