INTERNSHIP DETAILS

Physics | Data Science internship: wafer defectivity analysis

CompanyASML
LocationVeldhoven
Work ModeOn Site
PostedMay 20, 2026
Internship Information
Core Responsibilities
The intern will collect and analyze wafer defectivity data and system performance indicators to identify patterns and root causes. They will apply machine learning and statistical techniques to provide data-driven recommendations for improving system reliability.
Internship Type
full time
Company Size
35998
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Who are we? ASML is an innovation leader in the global semiconductor industry. We make machines that chipmakers use to mass produce microchips. Founded in 1984 in the Netherlands with just a handful of employees, we’ve now grown to over 40,000 employees, 143 nationalities and more than 60 locations around the world. What do we do? We provide chipmakers with hardware, software and services to mass produce patterns on silicon through lithography. Our lithography systems use ultraviolet light to create billions of tiny structures on silicon that together make up a microchip. We push our technology to new limits to enable our customers to create smaller, faster and more powerful chips. Who are our people? While you may think that only engineers and mathematicians work at ASML, you'll be surprised to find out that our people come from a wide variety of backgrounds. Across ASML, we have dedicated teams that manage customer support, communications and media, IT, software development and more. Every team in the company is essential for pushing our technology and the industry forward. If you love to tackle challenges and innovate in a collaborative, supportive and inclusive environment with all the flexibility and freedom to unleash your full potential, ASML is the place to be. Join us!
About the Role

Introduction

The EUV Wafer Defectivity team at ASML focuses on improving wafer quality in advanced lithography systems. In this internship you will help uncover how defects impact system performance. The team uses diagnostic data to trace defect sources and prevent recurring issues. Your work in this internship will combine data analysis and machine learning. This internship offers a hands-on opportunity to contribute to real engineering improvements.

Your assignment

In this internship you will study defectivity metrics and connect them to system performance indicators. You will work with large datasets and explore machine learning methods to identify patterns and root causes. Your insights will support engineers in improving system reliability and performance. 
Your main responsibilities will be:

  • Collect and structure wafer defectivity data and system performance indicators

  • Analyze defectivity metrics such as size and material composition

  • Apply statistical analysis to identify trends and correlations

  • Explore machine learning techniques to detect patterns and root causes

  • Collaborate with engineers and stakeholders to interpret data insights

  • Support performance analysis through data-driven recommendations

  • Present findings clearly to support technical decision-making

This is a master non-thesis internship for 6 months, 5 days per week (3-4 days on-site). The start date of this internship is as of September 2026.

Your profile

To be suitable for the internship, you:

  • Are pursuing a master’s degree in data science, physics, materials science, or a related field

  • Have experience with machine learning and statistical analysis techniques

  • Are analytical and able to structure complex datasets into clear insights

  • Communicate clearly in English, both written and verbal

  • Are proactive, collaborative, and comfortable working with diverse stakeholders

  • Have experience with MATLAB

This position requires access to controlled technology, as defined in the United States Export Administration Regulations (15 C.F.R. § 730, et seq.). Qualified candidates must be legally authorized to access such controlled technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.

Inclusion and diversity

ASML is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that inclusion and diversity is a driving force in the success of our company.

Need to know more about applying for a job at ASML? Read our frequently asked questions.

Key Skills
Machine LearningStatistical AnalysisData AnalysisMATLABRoot Cause AnalysisData StructuringPhysicsMaterials ScienceEnglish Communication
Categories
Data & AnalyticsEngineeringScience & ResearchTechnologyManufacturing