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INTERNSHIP DETAILS

Intern - PIE Yield Analysis (YA)

CompanyMicron Technology

LocationSingapore

Work ModeOn Site

PostedApril 6, 2026

Internship Information

Core Responsibilities

The intern will analyze structured engineering datasets to identify relationships between electrical test results and fabrication process metrics. They will develop data-driven insights and analytical frameworks to support yield learning and process improvement initiatives.

Internship Type

full time

Company Size

39360

Visa Sponsorship

Language

English

Working Hours

40 hours

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About The Company

Micron is 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 (AI) and compute-intensive applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience. To learn more about Micron Technology, Inc. (Nasdaq: MU), visit micron.com.

About the Role

Our vision is to transform how the world uses information to enrich life for all.

Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.

Location:

1 North Coast Drive, Singapore

Department:

Product Integration Engineering – Yield Enhancement

Project Title

3D NAND Yield Analytics Using Multivariate Data Analysis

Project Description

This internship project provides students with hands-on exposure to yield learning challenges in advanced 3D NAND technology. The intern will work on structured engineering datasets to explore the relationship between electrical test results and fabrication process metrics. Through this project, the intern will develop data-driven insights and analytics capabilities that support yield learning and process improvement initiatives within the semiconductor manufacturing environment.

The project is designed to be learning-focused and analytical in nature, providing exposure to semiconductor yield concepts, probe testing fundamentals, and modern data analysis techniques used in the industry.

Project Scope / Learning Opportunities

During this project, the intern will learn:

Fundamentals of probe testing methodology and electrical fail mode understanding
Relationship identification between electrical failures and fabrication process metrics
Application of multivariate data analysis techniques to large engineering datasets
Introduction to machine learning concepts for yield learning use cases
Practical use of Python for data analysis, visualization, and model development

Deliverables

A multivariate data analysis framework or tool developed using Python
Documented analysis highlighting potential yield opportunities and key correlations
Summary presentation outlining methodology, findings, and learning outcomes

Impact of Project

Enables structured yield learning through data-driven analysis
Provides reusable analytical approaches for future yield investigations
Develops intern capability in semiconductor data analytics and engineering problem solving

Skillset Required

Basic programming knowledge (Python preferred)
Interest in data analysis, statistics, or machine learning
Fundamental understanding of engineering concepts
Analytical thinking and problem-solving skills

Course of Interest

Electrical Engineering
Computer Engineering
Data Science
Semiconductor Technology
Related engineering or quantitative disciplines

Internship Period/Duration:

Aug - Dec 2026 /4 - 6 Months

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.

Key Skills

PythonData analysisStatisticsMachine learningElectrical engineeringSemiconductor technologyData visualizationModel developmentAnalytical thinkingProblem-solvingProbe testingMultivariate data analysis3D NANDYield enhancementEngineering metrics