AI-Driven Materials Research Engineer

Applied Materials, Inc.; Santa Clara (CA); On-site; USD 170,000 - 234,000; Full time

Job summary

Applied Materials is seeking an AI Materials Research Engineer to accelerate semiconductor materials discovery using Scientific AI, computational materials science, and machine learning. This role blends materials science with AI/ML, simulation, and data-driven modeling to develop next-generation materials and processes.

The position requires a PhD/MS in a related field, 2–5 years in computational materials science, and strong Python/ML skills.

Qualifications

• MS/PhD in Materials Science, Computational Materials Science, Physics, Chemical Engineering, or related field.
• 2–5 years of experience in Computational Materials Science, Materials Informatics, Scientific ML, or AI for scientific applications.
• Strong Python programming and ML experience (PyTorch, TensorFlow, Scikit-Learn).
• Experience with DFT, MD, kMC, Phase-Field Modeling.

Responsibilities

• Materials property prediction.
• Materials screening and optimization.
• Process-performance modeling.
• Generative materials design.
• Density Functional Theory (DFT).
• Molecular Dynamics (MD).
• Kinetic Monte Carlo (kMC).
• Phase-field and Monte Carlo simulations.
• Build AI surrogate models to accelerate simulation-driven research.
• Experimental data, characterization results, and simulation outputs review.
• Literature review and hypothesis generation.
• Experiment planning and simulation orchestration.
• Collaborate with materials scientists, process engineers, and AI teams.

Skills

Python programming

ML experience

PyTorch

TensorFlow

Scikit-Learn

Education

MS/PhD in Materials Science or related field

Tools

VASP

Quantum Espresso

CP2K

LAMMPS

GROMACS

Job description

Applied Materials is seeking an AI Materials Research Engineer to accelerate semiconductor materials discovery using Scientific AI, computational materials science, and machine learning. This role blends materials science with AI/ML, simulation, and data-driven modeling to develop next-generation materials and processes.

The position requires a PhD/MS in a related field, 2–5 years in computational materials science, and strong Python/ML skills.