Intern - PIE RDA

Project Title

Manufacturing Process Analytics and Equipment Shading Characterization Using Inspection Data

Project Description

This internship offers an opportunity to learn how data analytics is applied within a high-volume semiconductor manufacturing environment. The intern will be exposed to process monitoring concepts and statistical analysis methods through the study of historical manufacturing and inspection datasets.

The primary project focuses on collaborating with the Smart Manufacturing & Artificial Intelligence team to investigate equipment hardware-related shading phenomena observed in inspection data. The intern will analyze how shading patterns influence data quality and process control, and develop analytical insights to support long-term manufacturing improvement initiatives.

Through this project, the intern will gain hands-on experience in semiconductor manufacturing data, applied statistics, and cross-functional collaboration between process engineering and advanced analytics teams.

Objective of the Project

• Develop foundational understanding of semiconductor manufacturing process control and inspection data
• Apply data analytics techniques to identify systematic patterns and variations in large datasets
• Build analytical thinking and problem-solving skills in a real manufacturing context

Project Scope

• Study historical Statistical Process Control (SPC) data and inline defect datasets to understand process behavior
• Analyze defect and inspection data to identify recurring patterns, anomalies, and correlations
• Investigate and characterize equipment hardware-related shading effects using inspection datasets
• Perform data cleaning, feature extraction, and exploratory statistical analysis
• Examine relationships between shading signatures, equipment conditions, process steps, and defect characteristics
• Develop data visualizations or analytical methods to highlight shading trends and detection opportunities
• Participate in technical discussions with process engineering and analytics stakeholders to translate findings into insights

Learning Opportunities

• Exposure to semiconductor manufacturing operations and process control concepts
• Practical experience in data analytics, statistical analysis, and visualization
• Understanding how manufacturing challenges are approached using data-driven methods
• Experience working in a cross-functional engineering and analytics environment

Project Deliverables

• Process Analytics Summary
  • Key observations derived from SPC and defect data analysis
  • Analytical interpretation of observed process variations
• Shading Characterization Report
  • Quantitative analysis of shading patterns and contributing factors
  • Correlation of shading effects with equipment and process variables
• Data Visualization / Analytical Outputs
  • Charts, dashboards, or notebooks illustrating trends and shading signatures
  • Documentation of analytical approach and findings

Impact of Project

• Improved understanding of inspection data quality challenges
• Data-driven insights to support future process control and monitoring strategies
• Contribution to long-term manufacturing analytics capability development

Skillsets Required

• Basic understanding of data analysis and statistics
• Familiarity with at least one of the following tools:
  • Python
  • SQL
  • Microsoft Excel
• Strong analytical thinking and willingness to learn

Course of Interest

• Electrical or Electronic Engineering
• Mechanical Engineering
• Materials Science
• Semiconductor-related disciplines

About Micron Technology, Inc.

We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience.

To learn more, please visit micron.com/careers

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

To request assistance with the application process and/or for reasonable accommodations, please contact hrsupport_sg@micron.com

Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.

Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.

AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.

Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.