Statistical method | Internship: Bayesian methods for system-level qualification

ASML; Veldhoven; Hybrid; EUR 8,900 - 17,000; Full time

Job summary

ASML in Veldhoven invites a master’s student to join a data analytics internship focused on Bayesian methods for system-level overlay qualification. You will analyze datasets, build quantitative models, and translate findings into practical recommendations for engineering decisions.

The six-month, full-time internship offers hands-on experience in an international environment, with hybrid work and collaboration across experienced teams.

Qualifications

• Pursuing a master’s degree in a quantitative field (Statistics, Applied Math, Econometrics, Data Science).
• Experience with MATLAB and applying statistical modelling.
• Strong analytical and problem-solving skills.
• Fluent English communication.
• Willingness to relocate to the Netherlands.

Responsibilities

• Develop and validate a Bayesian proof-of-concept for system-level overlay qualification.
• Analyze complex datasets and evaluate model performance.
• Translate results into practical guidance for engineering decisions.
• Document methodology and provide future-use recommendations.
• Deliver validated tooling that works across multiple datasets, using MATLAB or bindings.

Skills

MATLAB experience

Analytical thinking

Problem-solving

English communication

Collaborative mindset

Education

Master's degree in Statistics / Applied Mathematics / Econometrics / Data Science

Tools

MATLAB

Job description

Introduction

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.

• Statistical method | Internship: Bayesian methods for system-level qualification
• Location: Veldhoven, Netherlands
• Team: Interns and Trainees
• Work experience: 0-1 year
• Educational background: Computer Science
• Educational background: Mathematics
• Educational background: Other technical backgrounds
• Travel: No
• Workplace type: Hybrid
• Fulltime/parttime: Full time

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

This is a master internship for 6 months, 5 days per week (3 days on-site). The start date of this internship is as of February 2027.

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.

Working at ASML means contributing to technology that enables innovation across industries worldwide. During the internship, you will gain hands-on experience, collaborate with diverse teams, and further develop your technical and professional skills.

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).

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.