Within ASML, you will join a team focused on solving complex business challenges through data-driven insights and quantitative analysis. The team supports decision-making by transforming data into actionable recommendations that improve processes and performance. During this internship, you will contribute to the development and evaluation of advanced statistical and mathematical models that help address real business questions. You will work together with experienced professionals in an innovative and international environment while applying your academic knowledge to real-world challenges. This internship offers an excellent opportunity to develop your analytical skills and create meaningful impact.
Your assignment
In this internship, you will support the team in analyzing complex datasets and developing quantitative models to improve decision-making. You will investigate statistical relationships, evaluate model performance, and translate findings into practical recommendations. The core of this assignment is to develop a proof of concept for applying Bayesian statistics to system-level overlay qualification and determine whether the approach provides sufficient practical benefit for use in our daily engineering work.
The internship provides an opportunity to apply advanced analytical techniques while working on business-relevant challenges.
Your main responsibilities will be:
- Familiarize yourself with overlay measurement data, performance metrics, machine populations, and current pre/post-change analysis practices;
- Develop and validate a proof-of-concept Bayesian statistical model for system-level overlay qualification.
- Evaluate the proposed approach using real measurement data, simulated data, or a combination of both;
- Compare the proposed methodology with current methods and translate the results into clear guidance for engineering decisions;
- Adequately document the underlying statistical methodology and provide recommendations for future use and developments;
- Implement and deliver validated tooling, which must work on multiple representative overlay datasets, to be selected during the assignment, rather than being optimized for one specific case.
- Develop the tooling in MATLAB, or provide MATLAB bindings if a different implementation is supported by sufficient technical justification
Your Profile
To be suitable for the internship, you:
- Are pursuing a master's degree in Statistics, Applied Mathematics, Econometrics, Data Science, or another closely related quantitative field.
- Have experience with MATLAB and applying statistical modelling techniques.
- Have knowledge of mathematical modelling and quantitative analysis methods.
- Demonstrate strong analytical and problem-solving skills.
- Are proactive, collaborative, and comfortable communicating in English.
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 for the duration of your internship. If you currently live or study outside the Netherlands, your CV or motivation letter must state your willingness to relocate;
- If you are a non-EU citizen studying in the Netherlands, your university must be willing to sign the documents required for the internship (i.e., the Nuffic agreement).
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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