Intern - NTI Process Integration - AI Track

Title

NTI NAND Process Integration (PI) Intern – AI Track

Role Overview

As a Process Integration (PI) intern on the Data Science / AI Track, you will apply data analytics, machine learning, and statistical modeling to accelerate process learning cycles and improve engineering decision‑making in advanced NAND technology development.

You will focus on extracting actionable insights from process, inline, and electrical datasets, and translating these insights into tools, analysis, and recommendations that can be directly used by PI engineers.

Key Responsibilities

• Build and evaluate data‑driven models to support 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 data mining and statistical evaluation of split outcomes (e.g., ANOVA‑style learning).
• Identify opportunities to accelerate process learning and improve PI efficiency through data‑driven insights.
• Liaise with Micron AI and Data Science partners to identify and drive efficiency improvements within the scope of PI.
• Communicate results with strong explainability (e.g., feature importance, sensitivity trends) and align findings with engineering intuition.
• Demonstrate strong analytical capability along with clear verbal and written communication skills, effectively engaging a wide range of audiences.
• Work independently with a high level of self‑motivation, time management, and prioritization skills.
• Deliver a complete intern project package, including code/notebooks, documentation, and presentation‑ready summaries.

Education and Experience

• Currently pursuing a Master or PhD in Electrical Engineering, Physics, Science, Mathematics, Computer Science, Materials Science, Data Science, Artificial Intelligence, or a related field, and available for a semester‑long internship.
• Demonstrated proficiency in Python, SQL, and data analysis.
• Experience with data analysis, statistics, machine learning, and statistical modeling to extract actionable insights from complex datasets is a strong plus.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the