Physicist/Scientist Machine Learning

Who We Are

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. 

What We Offer

Salary:

Location:

You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more. 

At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits. 

We are seeking a highly motivated MS or PhD‑level scientist or engineer to develop and apply machine learning–based models using data generated from multi‑dimensional, high‑performance computing (HPC) simulations. The successful candidate will work at the intersection of physics‑based modeling, large‑scale simulation, and modern AI/ML methods to accelerate product developing in the fast-paced semiconductor equipment industry. Focus will be on developing ML models based on plasma and electromagnetic simulations.

This role is ideal for candidates with strong domain knowledge in engineering or physical sciences and hands‑on experience translating complex simulation data into robust, predictive machine learning models.

Required Qualifications

• MS or PhD in Engineering (e.g., Chemical, Electrical, Mechanical, Aerospace, Nuclear, Materials), Science (e.g., Physics, Chemistry), or Computer Science
• Significant experience developing machine learning or deep learning models using data from multi‑dimensional numerical simulations (e.g., PDE‑based solvers, particle‑based simulations, multiphysics models)
• Strong background in Python‑based scientific computing and ML workflows
• Demonstrated experience with PyTorch or equivalent deep learning frameworks
• Solid understanding of:
  • Data preprocessing and feature engineering for large, high‑dimensional datasets
  • Model training, validation, and performance evaluation
  • Numerical methods and/or physics‑based modeling concepts

Preferred Qualifications

• Experience with NVIDIA Physics NeMo, NVIDIA Modulus, or related physics‑informed or simulation‑driven ML libraries
• Familiarity with GPU‑accelerated computing, CUDA‑aware workflows, and HPC environments
• Exposure to physics‑informed machine learning (PIML), surrogate modeling, reduced‑order modeling, or operator learning
• Publications or demonstrated research contributions in ML for physical systems or related fields

Key Responsibilities

• Develop and train machine learning and deep learning models using data from large‑scale, multi‑dimensional HPC simulations
• Collaborate with domain experts to incorporate physical constraints, scientific insight, and prior knowledge into ML model design
• Design workflows for data ingestion, curation, and analysis of high‑volume simulation outputs
• Evaluate model accuracy, generalization, and robustness across a wide range of operating conditions
• Optimize models for performance, scalability, and deployment on GPU‑accelerated platforms
• Contribute to internal software tools, modeling frameworks, and best practices

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 Accommodations_Program@amat.com, 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.