Intern - NTI Process Integration (AI Track)

About the role

Micron is offering an internship project for students to gain hands-on exposure to data analytics, machine learning and statistical modeling applied to Process Integration (PI) for advanced NAND technology development. The intern works on a defined project exploring how data-driven approaches support process learning, experimentation and engineering decisions, working with process, inline and electrical datasets.

Key responsibilities

• Build and evaluate data-driven models supporting PI outcomes such as cycle-time reduction, faster learning loops and process optimization.
• Perform statistical analysis of split experiments (e.g. DOE-related analysis), including data preparation, feature engineering and model interpretation.
• Conduct split-DOE and conversion analytics, including datamining and statistical evaluation of split outcomes (e.g. ANOVA-style learning).
• Identify ways to speed up process learning and improve PI efficiency through data-driven insights.
• Liaise with Micron AI and Data Science partners to drive efficiency improvements within the PI scope.
• Communicate results with strong explainability (feature importance, sensitivity trends) and align them with engineering intuition.
• Deliver a complete intern project package, including code/notebooks, documentation and presentation-ready summaries.

Required profile

• Currently pursuing a Master's or PhD in Electrical Engineering, Physics, Science, Mathematics, Computer Science, Materials Science, Data Science, Artificial Intelligence or a related field.
• Available for a semester-long internship.
• Strong analytical ability, clear verbal and written communication, and the ability to engage a wide range of audiences.
• Works independently with strong self-motivation, time management and prioritization.

Required skills

• Demonstrated proficiency in Python, SQL and data analysis.
• Experience with data analysis, statistics, machine learning and statistical modeling is a strong plus.