{"id":3684620,"url":"https://alion.io/job/asml-computer-science-data-science-internship-failure-pattern-analysis","title":"Computer Science | Data Science internship: failure pattern analysis","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":135,"ghost_share":0,"stale_share":0.83,"repost_share":0,"time_to_fill_p50_days":17,"computed_at":"2026-11-04T06:34:25Z"}},"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":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-11-03T14:26:51Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-04T07:29:04Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Introduction\nThe Leveling department within Development and Engineering at ASML develops advanced wafer measurement solutions that support nanometer-level accuracy in semiconductor manufacturing. This internship focuses on improving the understanding of machine failures through data-driven analysis of event logs. You will help transform complex and noisy machine data into meaningful insights that support system reliability and performance. Your work will contribute to identifying recurring failure patterns and enabling more effective failure classification. This internship offers the opportunity to combine artificial intelligence, machine learning, and data mining in a highly innovative engineering environment.\nYour assignment\nDuring this internship, you will develop methods to analyze machine event logs and identify patterns related to machine failures. You will design and evaluate machine learning approaches that classify failure modes and uncover valuable insights from historical machine data. The results of your work may support engineers in understanding failure behaviour across multiple systems and improving future diagnostics.\nYour main responsibilities will be:\nDevelop algorithms to clean, compress, and structure noisy machine event data.\nIdentify recurring failure signatures using data mining and machine learning techniques.\nBuild and evaluate supervised and unsupervised classification models.\nValidate findings using historical data and expert feedback.\nInvestigate similarities and differences between failure patterns across machines.\nAssess the practical value of the proposed solution for engineering use cases.\nPresent results and recommendations to engineers and researchers.\nThis is a master's thesis/non-thesis internship for a minimum of 6 months, 5 days per week (3 days on-site).\nThe start date of this internship is as of February 2027 or earlier, depending on your availability.\nYour profile\nTo be suitable for the internship, you:\nAre pursuing a master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Electrical Engineering, Systems & Control, or a related technical field.\nHave experience with Python and machine learning techniques.\nHave knowledge of data analysis, classification methods, feature engineering, and model evaluation.\nAre analytical and enjoy solving complex technical challenges using data.\nAre collaborative, proactive, and able to communicate technical findings clearly.\nThis internship is based in the Eindhoven region of the Netherlands. You will work closely with experienced engineers and researchers while contributing to meaningful challenges in the semiconductor industry. The assignment provides an opportunity to apply your academic knowledge to real-world engineering problems and gain hands-on experience in artificial intelligence, machine learning, and data-driven decision-making. If you are excited about turning complex data into actionable insights, we encourage you to apply for this internship.\nOther requirements you need to meet:\nYou are enrolled at an educational institute for the entire duration of the internship, and you are at least 18 years old at the start of the internship;\nIf 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);\nYou attach your cover letter with a clear motivation on why you are interested in this internship assignment in particular;\nYou need to be located in the Netherlands to be perform your internship. In case you are currently living/studying outside of the Netherlands, your application shows the willingness to relocate.\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.\nDo you want to know more about the internship allowance, visa support and applying for an internship at ASML? 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