Computer Science | Data Science internship: failure pattern analysis
Core
Develop methods to analyze machine event logs and identify patterns related to machine failures in semiconductor manufacturing equipment.
Role type
Master's thesis/non-thesis data science intern (failure pattern analysis)
Builds
Machine learning models for failure classification and event log analysis
Domain
Semiconductor manufacturing / Industrial IoT / Machine Reliability
Deliverable
production ML models
Required skills
Python, machine learning, data mining, supervised/unsupervised classification, feature engineering, model evaluation
Preferred skills
None stated
Technologies
Python
Responsibilities
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.
