Data Science Internship: ML for Failure Analytics

ASML US, LP. (US30); Veldhoven; Hybrid; EUR 10,000 - 15,000; Full time

Job summary

ASML in the Eindhoven region seeks a master's student for a data-driven internship focused on analyzing machine event logs to classify failures and improve diagnostics in semiconductor manufacturing. You will combine Python, ML, and data mining techniques on real engineering data, work with engineers, and present actionable insights to support reliability and performance improvements.

The role is a 6-month, 5-day-per-week commitment with 3 days on-site, offering exposure to AI/ML in a

Qualifications

• Pursuing a master's degree in Computer Science, Data Science, AI, ML, Applied Math, Statistics, or related field.
• Experience with Python and machine learning techniques.
• Knowledge of data analysis, classification methods, feature engineering, and model evaluation.
• Analytical and enjoy solving complex technical challenges using data.
• Collaborative, proactive, and able to communicate technical findings clearly.

Responsibilities

• Develop algorithms to clean, compress, and structure noisy machine event data.
• Identify recurring failure signatures using data mining and ML 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.

Skills

Python

Machine Learning

Data analysis

Feature engineering

Model evaluation

Communication

Collaboration

Programming

Education

Master's degree in Computer Science or related field

Tools

scikit-learn

pandas

Job description

ASML in the Eindhoven region seeks a master's student for a data-driven internship focused on analyzing machine event logs to classify failures and improve diagnostics in semiconductor manufacturing. You will combine Python, ML, and data mining techniques on real engineering data, work with engineers, and present actionable insights to support reliability and performance improvements.

The role is a 6-month, 5-day-per-week commitment with 3 days on-site, offering exposure to AI/ML in a