Intern - F10 Photo PEE: AI-Driven Quality Drift Detection

About the role

Micron's Fab 10 in Singapore is looking for an intern in its Photolithography Process and Equipment Engineering department. The project applies data analytics and machine learning to large-scale quality datasets to detect quality-metric drift faster, covering data querying, preprocessing, analytics, modelling and results visualization. High-performing interns may be considered for future full-time opportunities.

Key responsibilities

• Analyse large-scale quality, test and measurement datasets
• Explore machine learning techniques for feature selection, modelling and simulation
• Perform multivariable optimization and curve turning-point detection
• Develop analytical models for monitoring quality metrics and an early quality-drift detection methodology
• Create automated workflows and visualization tools that improve engineering productivity
• Deliver final project documentation and a presentation of methods, results, limitations and recommendations

Required profile

• Pursuing a degree in Engineering, Statistics, Mathematics, Computer Science, Data Science or a related discipline
• Ability to commit to a full-time internship of 5 months, January to May 2027
• Background in data analytics, statistics or large dataset interpretation

Required skills

• Programming in R, Python or a similar language
• Familiarity with machine learning, data visualization or optimization concepts
• Familiarity with AI tools, AI assistants or AI-enabled workflows is advantageous
• Strong analytical thinking and problem-solving skills