Physics AI Scientist

Overview

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

What you'll do

• 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.

Nice to have

• 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.

Details

• Location: Bangalore, India.
• Full time, assignee / regular employee type.
• Travel: yes, 10% of the time.
• Relocation eligible: yes.