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Principal AI Data Scientist – Scientific AI & Physics-Informed Machine Learning at Applied Materials - ApplyBlast

Principal AI Data Scientist – Scientific AI & Physics-Informed Machine Learning

Applied Materials

2 months ago

3.9 on Glassdoor

Santa Clara, California, United States

Onsite

Full Time

Senior

0 applicants

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About this role

The role involves developing and deploying advanced AI/ML solutions for semiconductor process and device simulations, creating physics-informed models, building surrogate models, and researching state-of-the-art techniques such as deep learning, generative AI, and graph neural networks. The candidate will collaborate with semiconductor experts, software engineers, and product teams to transition research into production solutions while contributing to patents, publications, and technical leadership.

Responsibilities

Develop and deploy advanced AI/ML solutions for semiconductor process and device simulations
Build surrogate models and scientific machine learning frameworks to accelerate computational workflows
Collaborate with semiconductor experts and product teams to transition research into production solutions

Skills

Qualifications

PhD in Electrical EngineeringPhD in PhysicsPhD in Materials SciencePhD in Computer SciencePhD in Applied Mathematics

About Applied Materials

appliedmaterials.com

Headquarters

Santa Clara, California, United States

Company Size

10001+ employees

Founded

1967

View Profile

Applied Materials is a global leader in materials engineering solutions that enable the production of virtually every new semiconductor chip and advanced display. The company designs, manufactures and services equipment, software and process technologies across semiconductor fabrication (deposition, etch, implantation, inspection/metrology, CMP, ALD/CVD/PVD), advanced packaging and display manufacturing. Its customers include chipmakers, foundries and display manufacturers worldwide, and it provides process integration, factory automation and lifecycle services to improve yield, performance and cost. Headquartered in Santa Clara, California, Applied Materials combines deep R&D and scale to drive device scaling, energy efficiency and new architectures.