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AI Materials Research Engineer

Applied Materials
Santa Clara, USA
Full-time
Junior · 2–5 years experience
Onsite
Discovered 3 weeks ago
pythonpytorchscikit-learntensorflow

Full Job Posting

Role Summary

Applied Materials is seeking an AI MaterialsResearch Engineer to accelerate semiconductor materials discovery using Scientific AI, Computational MaterialsScience, and Machine Learning. The role combines materials science expertise with AI/ML, simulation, and data-driven modeling to develop next-generation materials and process innovations. Based on related internal Materials AI role descriptions.

Key Responsibilities

Develop AI/ML models for:

Materials property prediction

Materials screening and optimization

Process-performance modeling

Generative materials design

Apply computational materialsmethodologies including:

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.

Create materials informatics pipelines integrating:

Experimental data

Characterization results

Simulation outputs

Scientific literature

Develop AI copilots and agentic workflows for:

Literature review

Hypothesis generation

Experiment planning

Simulation orchestration

Collaborate with materials scientists, process engineers, and AI teams to deliver Scientific AI solutions.

Required 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 one or more computational methods:
  • DFT
  • MD
  • kMC
  • Phase-Field Modeling
  • Strong understanding of:
  • Crystal structures
  • Thermodynamics
  • Kinetics
  • Defect physics
  • Semiconductor materials

Preferred Qualifications

  • Experience with simulation platforms such as VASP, Quantum Espresso, CP2K, LAMMPS, or GROMACS.
  • Experience with Materials Project, OQMD, NOMAD, or similar databases.
  • Familiarity with:
  • Graph Neural Networks (GNNs)
  • Materials Foundation Models
  • Physics-Informed ML
  • Generative AI for materials design
  • Experience using cloud/HPC environments for large-scale model training and simulations.
  • Additional Information
  • Time Type:
  • Employee Type:
  • Travel:
  • Relocation Eligible:
  • The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.
  • For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.
  • Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.
  • In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at [email protected], or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.

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