Intern - NAND Cell Reliability

Micron; Singapore; On-site; SGD 13,000 - 27,000; Full time

Job summary

Micron Technology, Singapore invites an AI-Enabled NAND Reliability Data Analytics and Technology Learning Intern to join the TD - NAND Reliability team for a 6-month internship. You will work under mentors, perform data-driven analysis on NAND reliability, develop visualizations, and explore AI-enabled techniques to improve engineering learning and efficiency.

Candidates pursuing a PhD in related fields are preferred.

Qualifications

• Strong analytical, critical-thinking, and problem-solving abilities.
• Effective written and verbal communication skills.
• Familiarity with data analysis, statistics, and data visualization techniques.

Responsibilities

• Analyze reliability datasets to investigate sources of variation.
• Develop visualizations and technical summaries to communicate findings.
• Apply statistical and data-driven methodologies to identify trends and learning opportunities.
• Explore AI-Enabled analytical techniques to improve data interpretation and insight generation.
• Develop or enhance analysis workflows, scripts, or tools that improve reproducibility.
• Utilize Python and data analysis tools to streamline engineering learning cycles.
• Collaborate with mentors and project stakeholders.

Skills

Analytical skills

Critical thinking

Problem solving

Written communication

Verbal communication

Data visualization

Python programming

AI interest

Team collaboration

Education

PhD in Electrical/Electronics/Materials/Applied Physics/Semiconductor Engineering

Tools

Python

Jupyter notebooks

Data analysis tools

Job description

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 Singapore Department Technology Development (TD) - NAND Reliability Project Title AI-Enabled NAND Reliability Data Analytics and Technology Learning Intern

Project Description As an Intern, you will work under the guidance of experienced mentors and collaborate with project stakeholders to complete a structured technical project focused on NAND memory reliability learning and data analytics. The internship provides hands-on exposure to semiconductor reliability methodologies, data-driven engineering practices, and cross-functional collaboration. The project is designed to deliver meaningful learning opportunities while contributing to technology understanding and engineering effectiveness.

Objective of the Project

The objective of this project is to enhance understanding of NAND reliability behavior through data-driven analysis, identify sources of variation and reliability trends, and explore automation or AI-Enabled approaches that improve engineering learning, analytical efficiency, and technical decision-making.

Project Scope

Reliability Data Analysis and Variation Learning

• Analyze reliability datasets to investigate sources of variation, including die-level, block-level, and wordline-level behaviors.
• Develop visualizations and technical summaries to communicate findings and support technology learning.
• Apply statistical and data-driven methodologies to identify trends, patterns, and learning opportunities.
• Explore AI-Enabled analytical techniques to improve data interpretation and insight generation.

Intrinsic Cell Reliability Learning Project

• Participate in a structured learning project related to intrinsic cell reliability concepts and qualification methodologies.
• Examine reliability indicators, error behavior characteristics, and learning metrics relevant to NAND technology development.
• Collaborate with mentors to understand how reliability data informs qualification readiness and technology learning.

Automation and AI-Enabled Efficiency Improvement

• Develop or enhance analysis workflows, scripts, or tools that improve reproducibility and reduce manual effort.
• Utilize Python and data analysis tools to streamline engineering learning cycles.
• Explore opportunities to leverage AI-enabled tools where appropriate to improve productivity and data analysis efficiency.

Learning Opportunities

• Learn how NAND memory reliability is evaluated, including bit errors, error behavior, and reliability mechanisms.
• Develop data analytics and problem-solving skills through real engineering datasets.
• Understand how engineering teams accelerate technology learning through data-driven methodologies and efficiency improvements.
• Gain experience working with cross-functional teams across Technology Development, Characterization, and Validation organizations.

Deliverables

• A defined project plan outlining objectives, methodology, timeline, assumptions, and project risks.
• A final technical presentation summarizing project approach, analysis, findings, conclusions, and recommendations.
• A concise technical report documenting project outcomes and key learnings.
• Reproducible analysis artifacts, such as scripts, notebooks, workflows, or automation tools, with appropriate documentation.
• Knowledge-transfer documentation to support future learning and project continuity.

Impact of the Project

The project aims to contribute to improved understanding of NAND reliability behavior, accelerate technology learning, strengthen analytical capabilities, and identify opportunities for efficiency improvements through data analytics, automation, and AI-Enabled engineering solutions.

Skillsets Required

• Strong analytical, critical-thinking, and problem-solving abilities.
• Effective written and verbal communication skills.
• Familiarity with data analysis, statistics, and data visualization techniques.
• Programming experience in Python or a similar analytical programming language is preferred.
• Interest in semiconductor technologies, reliability engineering, or data-driven engineering applications.
• Curiosity and willingness to explore Artificial Intelligence (AI), Generative AI, AI Assistants, Agentic AI, Agentic Solutions, LLMs, or other AI-Enabled tools.
• Ability to work effectively in a collaborative and project-based learning environment.

Course of Interest

The ideal candidate should be pursuing a PhD in Electrical Engineering, Electronics Engineering, Materials Engineering, Applied Physics, Semiconductor Engineering, or a related discipline.

Duration of Period

The ideal candidate should be able to commit to a full-time internship period of 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 [e-mail]

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.