2025 Fall - Physicist/Scientist Co-Op

Job description: 

Our team focuses on screening and designing new chemistries and materials for R&D prior to deployment in high volume manufacturing on Applied Materials tools for a wide variety of logic and memory technologies.  We aim to narrow and accelerate the iterative experimental R&D process.  This position requires specialized depth and/or breadth of expertise in developing, preparing, submitting, and analyzing computational models at the atomic scale leveraging a combination of Ab-initio, Molecular Dynamics, Artificial Intelligence, and Machine Learning techniques. The internship will focus on an already identified needs for new materials and chemistry to enable deposition of materials to meet specific material property targets.  There will have flexibility in scoping and recommending what other software tools and methodologies should also be explored to determine how to be meet the material and chemistry property prediction needs.

Key Responsibilities:

• Chemistry and materials design for screening and optimization applications with special emphasis on at least one of the following areas: thermal transport, polymer materials formation and viscosity, low and high dielectric materials, work function metals, precursor design for purity of deposition, and selectivity in etch chemistry
• Scope the diverse cutting-edge materials and chemistry discovery tools on the market for potential future value and prioritize what methods warrant further exploration
• Evaluate a variety of MLIP’s for validation required property prediction and potential extend to fine-tuning of MLIP’s for increased accuracy.
• Recommend atomic-scale changes to structure and/or processing conditions to influence observed properties
• Provide parameters, inputs, and/or guidance for higher-level process, feature, and reactor models
• Hypothesize and test mechanisms to determine the root-cause of observed behavior
• Work effectively with external vendor software providers in testing new features and functionality of new products
• Work effectively with internal multi-disciplinary teams of experimentalists, modelers, and computing infrastructure support teams
• Demonstrate analytical and engineering judgement to scope and assess the appropriate level of model required
• Proactively validate/correlate results with real world data to improve models
• Present complex in-depth technical material in a concise manner
• Advocate for the power of modeling while also communicating limitations
• Serve as a business unit chemistry, materials, or physics expert

Minimum Qualifications:

• Must have a PhD or Master’s degree in Material Science, Chemical Engineering, Mathematics, Physics, or a related field with an availability range between August 2025 – Dec 2025
• Experience or academics with:
  • First Principles/Ab-initio/Density Functional Theory (local orbital and plane wave), Molecular Dynamics, and/or Monte Carlo methods
  • Machine learning interatomic potentials both at the training stage and inference stage.  Experience with both universal and focused approaches a plus.
  • Programming (Python, C, Fortran, etc.), scripting (python, Linux), and databases
• Knowledge of informatics, artificial intelligence, machine learning, and data science approaches

Preferred Qualifications:

• Polymer structure creation to property prediction such as viscosity
• Inverse design
• Enumerative atomic structure model prediction (diffusion models and beyond)
• Multi-step reaction network discovery
• Materials and/or chemistry discovery
• Virtualization

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Applied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All 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.