INTERNSHIP DETAILS

Data Science / Optimization Intern

CompanyApplied Materials
LocationAustin
Work ModeOn Site
PostedApril 8, 2026
Internship Information
Core Responsibilities
Develop and apply machine learning models and optimization algorithms for semiconductor hardware and recipe tuning. Collaborate with engineers to translate complex physical problems into data-driven workflows and document findings for technical stakeholders.
Internship Type
full time
Company Size
30663
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Applied Materials is the leader in materials engineering solutions that are at the foundation of virtually every new semiconductor and advanced display in the world. The technology we create is essential to advancing AI and accelerating the commercialization of next-generation chips. At Applied, we push the boundaries of science and engineering to deliver material innovation that changes the world. We look forward to engaging with you on compelling topics about the semiconductor industry. We want to hear from you, but offensive comments that create an unpleasant environment for our community will be removed. Thanks for your understanding.
About the Role

Who We Are

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. 

What We Offer

Location:

Austin,TX, 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. 

Role Overview

We are seeking highly motivated Data Science / Optimization Interns to work on AI‑driven recipe and hardware optimization problems in semiconductor process applications. The role focuses on developing and applying machine learning and optimization techniques using physics‑informed and data‑driven surrogate models, with mentorship and training provided by experienced engineers and data scientists.

Responsibilities

  • Develop and apply machine learning models for surrogate modeling of physical and engineering systems
  • Support optimization algorithms for recipe and hardware parameter tuning
  • Analyze simulation and experimental data to improve model accuracy and performance
  • Build Python‑based workflows for model training, inference, and evaluation
  • Collaborate with engineers and scientists to translate engineering problems into data‑driven models
  • Document methods and results and present findings to technical stakeholders

Required Qualifications

  • Currently pursuing a Bachelor’s degree in:
    • Computer Science
    • Data Science
    • Electrical, Mechanical, or Chemical Engineering
    • Applied Mathematics or a related technical field
  • Strong programming skills in Python
  • Understanding of machine learning fundamentals
  • Coursework or hands‑on experience in optimization, numerical methods, or scientific computing
  • Ability to work with data, debug models, and learn quickly

Preferred Qualifications

  • Exposure to optimization techniques (e.g., gradient‑based methods, Bayesian optimization)
  • Experience working with simulation or experimental data
  • Familiarity with NumPy, SciPy, scikit‑learn, or PyTorch
  • Interest in applied engineering or manufacturing problems

What You’ll Gain

  • Hands‑on experience applying AI and optimization to real‑world engineering problems
  • Exposure to physics‑informed machine learning and surrogate modeling
  • Opportunity to work on advanced optimization problems in semiconductor manufacturing
  • Close mentorship and technical growth in an R&D environment

Additional Information

Time Type:

Full time

Employee Type:

Intern / Student

Travel:

No

Relocation Eligible:

No

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 Accommodations_Program@amat.com, 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.

Key Skills
PythonMachine learningOptimizationData scienceNumerical methodsScientific computingSurrogate modelingNumPySciPyScikit-learnPyTorchData analysisAlgorithm developmentSemiconductor process applicationsPhysics-informed machine learning
Categories
TechnologyData & AnalyticsEngineeringScience & ResearchManufacturing
Benefits
Health and wellbeing programsProfessional growth supportBonus programStock award program