Physics AI Scientist

Applied Materials India; Bengaluru; On-site; INR 1,500,000 - 3,000,000; Full time

Job summary

Applied Materials India seeks a PhD-level AI scientist to develop next-generation AI models for semiconductor engineering, combining domain knowledge with modern ML.

You will build physics-aware surrogate and foundation models, and optimize workflows that accelerate simulation and design. Collaboration with domain experts is essential, as is contributing to scalable data pipelines and model deployment.

Qualifications

• Ph.D. in a related field is required.
• Strong background in scientific ML and numerical simulation is essential.
• Experience with surrogate modeling, PINNs, operator learning, or foundation models is preferred.
• Proficiency in Python and PyTorch is required.
• Experience with HPC, distributed training, and large-scale ML workflows is advantageous.

Responsibilities

• Develop scientific AI models bridging computing, physics simulations and ML.
• Train surrogate and foundation models for scientific simulations.
• Collaborate with domain experts to formulate AI solutions for engineering challenges.
• Create scalable data generation, training, validation and deployment pipelines.
• Publish innovations and drive adoption of Scientific AI across engineering apps.

Skills

Scientific ML

Numerical simulation

HPC

Distributed training

Foundation models

Education

Ph.D. in Mechanical Engineering

Ph.D. in Chemical Engineering

Ph.D. in Materials Science

Ph.D. in Physics

Ph.D. in Applied Mathematics

Ph.D. in Computer Science

Tools

Python

PyTorch

FNO

PINNs

Surrogate modeling

Job description

Who We Are

Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next‑generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world’s technology.

What We Offer

Location: Bangalore,IND

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.

Role Summary

Develop next-generation AI models for semiconductor engineering by combining scientific domain knowledge with modern machine learning. Build physics‑aware surrogate models, foundation models, and optimization workflows that accelerate simulation and engineering design.

Key Responsibilities

• Develop Scientific AI models that bridge scientific computing, physics‑based simulation and machine learning for physics and chemistry‑based engineering problems.
• Design and train surrogate models, operator‑learning models, and foundation models for scientific simulations.
• Collaborate with domain experts to formulate AI solutions for complex engineering challenges.
• Develop scalable data generation, training, validation and deployment workflows for Scientific AI models.
• Publish technical innovations and drive adoption of Scientific AI across engineering applications.

Preferred Qualifications

• Ph.D. in Mechanical Engineering, Chemical Engineering, Materials Science, Physics, Applied Mathematics, Computer Science, or a related field.
• Strong background in scientific machine learning and numerical simulation.
• Experience with surrogate modeling, PINNs, operator learning (e.g., FNO), or foundation models.
• Proficiency in Python and PyTorch.
• Experience with HPC, distributed training, large‑scale scientific datasets or scalable ML workflows.

Additional Information

Time Type: Full time

Employee Type: Assignee / Regular

Travel: Yes, 10% of the Time

Relocation Eligible: Yes

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.