In the Wafer Defectivity team at ASML, we strive to minimize the amount of dust particles deposited onto silicon wafers. These dust particles can cause (partial) malfunctions in the final product: the computer chip. We identify particle sources in our NXE system and implement structural solutions to prevent such issues.
 

The goal of this assignment is to study different metrics of wafer defectivity qualification tests, including size, material composition, etc., and do root-cause finding using Machine Learning techniques to identify defect sources that could impact scanner performance. Machine learning techniques need to be introduced to correlate defectivity performance parameters with other scanner performance KPI reports. Hence, your tasks for this assignment may include:

Collect data and scanner KPIs;

Analyze different metrics of wafer qualification test data;

Collaborate with several stakeholders for scanner KPI analysis and support engineers;

Explore Machine Learning techniques to study correlation between metrics of wafer qualification data and scanner performance KPIs;

Reporting out results to key stakeholders within departments for technical decision making.

 
This is a Master internship (non-thesis) for at least 6 months, minimum 4 days per week (3 days onsite). The start date of this internship is around January/February 2026.
 

To be a match for this internship, you:

Are a master student in Physics, Materials Science, Chemical Engineering, or Data Science;

Possess MATLAB or Python programming language skills (a plus);

Have strong knowledge in statistical analysis, regression analysis, and Machine Learning techniques;

Have strong problem solving skills and the ability to take initiative;

Have an analytical mindset and good communication skills in English (verbal and written).

Other requirements you need to meet:

You are enrolled at an educational institute for the entire duration of the internship;

You are located in the Netherlands to perform your internship. In case you are currently living/studying outside of the Netherlands, your CV/motivation letter includes the willingness to relocate;

If you are a non-EU citizen, studying in the Netherlands, your university is willing to sign the documents relevant for doing an internship (i.e., Nuffic agreement).

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.

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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