- Location
- Bengaluru, KA,IN, IN
- Type
- Full-time
- Department
- Education
- Education
- PhD
- Source
- Eightfold
Description
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.
## Qualifications
### Education:
Bachelor's Degree
### Skills
### Certifications:
### Languages:
### Years of Experience:
4 - 7 Years
### Work Experience:
## Additional Information
###
### Shift:
Day (India)
###
### Travel:
Yes, 10% of the Time
###
### Relocation Eligible:
Yes
### Referral Payment Plan:
Employee Referral (Standard)
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.