Physics | Data Science internship: wafer defectivity analysis, Veldhoven
Physics | Data Science internship: wafer defectivity analysis, Veldhoven
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5500 Veldhoven, Nederland
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Geplaatst op: 1 week geleden
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Onthouden
Advertentietekst
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.
Responsibilities
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 insightsSupport 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
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
Legal and Authorization 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.
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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.
Responsibilities
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 insightsSupport 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
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
Legal and Authorization 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.
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Belangrijke informatie
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BedrijfsnaamASML
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PositiePhysics | Data Science internship: wafer defectivity analysis
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Wees op je hoede, als het salaris voor de baan veel hoger is dan gebruikelijk.
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Physics | Data Science internship: wafer defectivity analysis is geplaatst in de Veldhoven stages, afstudeeropdrachten rubriek op Locanto.
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