{"id":3770809,"url":"https://alion.io/job/asml-statistical-method-internship-bayesian-methods-for-system-level-qualification","title":"Statistical method | Internship: Bayesian methods for system-level qualification","company":{"id":17151,"name":"ASML","domain":"asml.com","url":"https://alion.io/company/asml","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":84,"open_postings":140,"ghost_share":0,"stale_share":0.821,"repost_share":0,"time_to_fill_p50_days":18,"computed_at":"2026-11-06T05:58:05Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Veldhoven, Netherlands"],"countries":["NL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"MATLAB","optional":false}],"status":"live","first_seen_at":"2026-11-04T21:30:36Z","employer_posted_date":"2026-11-04","last_verified_at":"2026-11-06T08:04:26Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Introduction\nWithin 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.\nYour assignment\nIn 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.\nThe internship provides an opportunity to apply advanced analytical techniques while working on business-relevant challenges.\nYour main responsibilities will be:\nFamiliarize yourself with overlay measurement data, performance metrics, machine populations, and current pre/post-change analysis practices; \nDevelop and validate a proof-of-concept Bayesian statistical model for system-level overlay qualification. \nEvaluate the proposed approach using real measurement data, simulated data, or a combination of both; \nCompare the proposed methodology with current methods and translate the results into clear guidance for engineering decisions; \nAdequately document the underlying statistical methodology and provide recommendations for future use and developments;\nImplement 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.\nDevelop the tooling in MATLAB, or provide MATLAB bindings if a different implementation is supported by sufficient technical justification\nThis 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.\nYour Profile\nTo be suitable for the internship, you:\nAre pursuing a master's degree in Statistics, Applied Mathematics, Econometrics, Data Science, or another closely related quantitative field.\nHave experience with MATLAB and applying statistical modelling techniques.\nHave knowledge of mathematical modelling and quantitative analysis methods.\nDemonstrate strong analytical and problem-solving skills.\nAre proactive, collaborative, and comfortable communicating in English.\nWorking 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.\nOther requirements you need to meet:\nYou are enrolled at an educational institute for the entire duration of the internship; \nYou 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;\nIf 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).\nThis 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.\nInclusion and diversity\nASML 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.\nNeed to know more about applying for a job at ASML? 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