About this role
Computer Science | Data Science internship: failure pattern analysis Beschrijving Introduction The 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.
- Your assignment During 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.
Your main responsibilities will be
- Develop algorithms to clean, compress, and structure noisy machine event data.
- Identify recurring failure signatures using data mining and machine learning techniques.
- Build and evaluate supervised and unsupervised classification models.
- Validate findings using historical data and expert feedback.
- Investigate similarities and differences between failure patterns across machines.
- Assess the practical value of the proposed solution for engineering use cases.
- Present results and recommendations to engineers and researchers.
This is a master's thesis/non-thesis internship for a minimum of 6 months, 5 days per week (3 days on-site). The start date of this internship is...