Intern F10 Quality – Cell Wafer Level Reliability

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 N Coast Dr Fab10N Singapore

• Department: Quality Engineering Management (QEM)

• Project Title: AIEnabled System Intrinsic Reliability Prediction at Front-end

• Project Description: This project will focus on Cell Wafer Level Reliability (cWLR) in a semiconductor wafer fabrication environment with an emphasis on fastturn intrinsic cell reliability evaluation for process conversion device trim assessment and Outgoing Quality Reliability Monitoring (OQRM). The project will involve translating systemlevel intrinsic reliability metrics into meaningful waferlevel proxy metrics such as trigger rate and raw bit error rate (RBER) through test addition Machine Learning (ML) models will be applied to predict RBER across full baselines enabling smart sampling earlier visibility of intrinsic reliability performance at the High Volume Manufacturing (HVM) stage and the development of a faster scalable and more effective intrinsic issue detection approach to safeguard production quality.

• Scope: In this project the intern will

  - Learn advanced NAND cell waferlevel reliability testing flows and methodologies

  - Understand semiconductor reliability failure mechanisms and device physics

  - Partner with crosssite and crossfunctional teams to develop and implement cWLR test programs aligned with shiftleft initiatives

  - Support NAND product characterization experimentation and data analysis to develop cWLR solutions for product issues

  - Apply Machine Learning techniques to model and predict NAND cell intrinsic reliability performance

  - Analyze large datasets to enable smart sampling strategies and early intrinsic risk detection

• Deliverables: The intern will be able to:

  - Understand NAND memory functions and operations

  - Gain handson experience in probe testing and cWLR testing

  - Develop a systemlevel intrinsic reliability RBER predictor using waferlevel data

  - Contribute to datadriven reliability assessment methodologies used in HVM

• Impact of Project: Improved product quality control

• Skillsets Required:Problem solving data analytics Python

• Course of interests: Bachelors/Masters Degree in Electrical/Electronic Engineering Microelectronic would be preferred

• Duration Period: Minimum 5 months creditbearing fulltime internship from July to November 2026.

About Micron Technology Inc.

We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich lifefor 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.

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