AI Materials Research Engineer

Applied Materials
Santa Clara
Workplace: OnsiteFull timeUSD 170,000 - 234,000 annuallyFunction: Research & Scientific (R&D)Experience: 2-5 yearsEducation: mastersSkills: ["Collaboration","Innovation"]

Develop AI/ML models to accelerate semiconductor materials discovery, including property prediction, materials screening, process-performance modeling, and generative materials design. Apply computational methods such as DFT, molecular dynamics, kMC, and phase-field/Monte Carlo simulations, then build surrogate models and materials informatics pipelines that integrate experimental data, simulations, and literature. Create AI copilots/agentic workflows and collaborate with materials scientists, process engineers, and AI teams.

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FursaFursa
Applied Materials
Applied Materials
1 week ago

AI Materials Research Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 36 minutes agoStatus: Live

Job Summary

Develop AI/ML models to accelerate semiconductor materials discovery, including property prediction, materials screening, process-performance modeling, and generative materials design. Apply computational methods such as DFT, molecular dynamics, kMC, and phase-field/Monte Carlo simulations, then build surrogate models and materials informatics pipelines that integrate experimental data, simulations, and literature. Create AI copilots/agentic workflows and collaborate with materials scientists, process engineers, and AI teams.
Location: Santa Clara
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Develop AI/ML models for materials property prediction, materials screening and optimization, process-performance modeling, and generative materials design.
  • •Apply computational materials methodologies including DFT, MD, kMC, and phase-field/Monte Carlo simulations.
  • •Build AI surrogate models and create materials informatics pipelines integrating experimental data, characterization results, simulation outputs, and scientific literature.
  • •Develop 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.

Pay and Benefits

Salary: USD 170,000 - 234,000 annually
Perks:Travel Allowance

Key Requirements

  • •MS/PhD in Materials Science, Computational Materials Science, Physics, Chemical Engineering, or a 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 computational methods including DFT, MD, kMC, and Phase-Field Modeling.
  • •Strong understanding of crystal structures, thermodynamics, kinetics, defect physics, and semiconductor materials.
Experience:2-5 years
Education:Master's in Materials Science, Computational Materials Science, Physics, Chemical Engineering
Skills:CollaborationInnovation
Tech Stack:PythonPyTorchTensorFlowScikit-LearnDensity Functional Theory (DFT)Molecular Dynamics (MD)Kinetic Monte Carlo (kMC)Phase-field modelingMonte Carlo simulationsVASPQuantum EspressoCP2KLAMMPSGROMACSMaterials ProjectOQMDNOMADGraph Neural Networks (GNNs)Materials Foundation ModelsPhysics-Informed ML

Company Brief

Applied Materials
Provides semiconductor manufacturing equipment, services, and software used to build advanced chips and display technologies. Its tools support materials engineering, deposition, etching, inspection, and process control for major electronics manufacturers worldwide.
Industry: Industrial Machinery
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1967
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