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Salary
$154k – $329k per year (Estimated)
Location
In office (Santa Clara)
Seniority
Principal · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Applied Materials is a global materials engineering company for the semiconductor, flat panel display, and solar industries, headquartered in Santa Clara, California, and founded in 1967. The company provides specialized equipment, services, and software used to manufacture semiconductor chips, liquid crystal displays, and organic light-emitting diode screens. Operating in more than 20 countries across North America, Europe, and Asia, the publicly traded corporation serves major electronics manufacturers and focuses on advancing nanotechnology and energy-efficient electronics.

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

Salary:

$0.00 - $0.00

Location:

Santa Clara,CA

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.

Key Responsibilities

  • Develop and deploy advanced AI/ML solutions for semiconductor process and device simulations, Electronic Design Automation (EDA), packaging, reliability, and manufacturing applications.

    Create physics-informed and hybrid AI models that integrate experimental data, simulation outputs, and domain knowledge.

  • Build surrogate models and scientific machine learning frameworks to accelerate computationally intensive simulations and engineering workflows.

  • Research and apply state-of-the-art techniques including deep learning, generative AI, graph neural networks, neural operators, and foundation models.

  • Collaborate with semiconductor experts, software engineers, and product teams to transition research into production solutions.

  • Drive innovation through patents, publications, and technical leadership across STM and Applied Materials.

  • Effective technical verbal/written communication representing the org with limited supervision. Ability to collaborate with internal stakeholders, customers and vendors.
  • Able to follow complex program schedules, budgets, and milestones with limited supervision.
  • Collaborates/participate in discussions to solve interdisciplinary technical issues in a cross-functional team environment.

Required Qualifications

  • PhD in Electrical Engineering, Physics, Materials Science, Computer Science, Applied Mathematics, Computational Science, or related discipline.

  • Strongexpertisein machine learning, deep learning, statistical modeling, and scientific computing.

  • Hands-on experience with Python and modern AI frameworks such asPyTorch, TensorFlow, or JAX.

  • Strong background in numerical methods, optimization, simulation, or computational modeling.

  • Excellent communication skills and ability to work across multidisciplinary teams.

Preferred Qualifications

  • Semiconductor industry experience in process, device, reliability, metrology, packaging, EDA, or manufacturing.

  • 5+ years of experience developing advanced AI/ML algorithms for scientific or engineering applications.

  • Experience with Physics-Informed Neural Networks (PINNs), neural operators, surrogate modeling, uncertainty quantification, or digital twins.

  • Familiarity with TCAD, FEM, CFD, Monte Carlo,multiphysicssimulation, or scientific computing environments.

  • Experience with foundation models, generative AI, multimodal learning, or graph neural networks.

  • Strong publication and/or patent recorddemonstratingtechnical innovation and thought leadership. The backgroundwe'retargeting issimilar tosenior researchers who combine semiconductor device physics, computational modeling, and advanced AI research

Additional Information

Time Type:

Full time

Employee Type:

Assignee / Regular

Travel:

Yes, 10% of the Time

Relocation Eligible:

Yes

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 [email protected],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.

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