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

StudentJob; Veldhoven; Hybrid; EUR 13,000 - 20,000; Full time

Job summary

ASML zoekt een masterstagiair data-analyse die Bayesian statistiek toepast op system-level overlay-kwalificatie. Je werkt aan modellering, evaluatie met realistische datasets en levert hulpbronnen die opgeschaald kunnen worden naar engineering-beslissingen.

De stage is 6 maanden, 5 dagen per week met 3 dagen on-site. Startdatum februari 2027. Je hebt een master-opleiding in statistiek/kwantitatieve velden en sterke MATLAB-ervaring.

Qualifications

• Bezig met een master die aansluit bij statistiek en data science.
• Ervaring met MATLAB en statistische modellering.
• Kennis van wiskundige modellering en kwantitatieve analysemethoden.
• Uitstekende analytische en probleemoplossende vaardigheden.
• Proactief, samenwerkend en communicatief in het Engels.

Responsibilities

• Vertrouwd raken met overlaymeetgegevens, prestatie-indicatoren en huidige analyses.
• Ontwikkelen en valideren van een proof-of-concept Bayesian statistisch model voor systeem-niveau overlaykwalificatie.
• Evalueren van de voorgestelde aanpak met echte/simuleerde data en eventueel combinatie.
• Vergelijken met huidige methodes en vertalen naar duidelijke engineering-adviezen.
• Documenteren van de statistische methodologie en aanbevelingen voor toekomstig gebruik.
• Implementeren en leveren van gevalideerde tooling die op meerdere datasets werkt, met MATLAB-bindingen indien nodig.
• Ontwikkelen van tooling in MATLAB, of MATLAB-bindingen leveren bij voldoende onderbouwing.

Skills

Analytisch denkvermogen

Engelse communicatie

Statistische modellering

Kwantitatieve analysemethoden

Probleemoplossend vermogen

Education

Master 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.

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.

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.

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.

Need to know more about applying for a job at ASML? Read our frequently asked questions.

Salarisomschrijving

In overeenstemming

Dienstverband:

Vaardigheden

• Je beheerst Engels

Opleiding

HBO