Physics | Data Science internship: wafer defectivity analysis

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 target="_blank">frequently asked questions.