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Micron Technology

Makes memory and storage chips for AI and PCs

NAND Cell Reliability Intern - AI-Enabled NAND Reliability Data Analytics and Technology Learning

Data AnalysisPosted on Nov 12
InternshipSingaporeNo salary listedIn-person

About the Job

Requirements

  • The ideal candidate should be pursuing a PhD in Electrical Engineering, Electronics Engineering, Materials Engineering, Applied Physics, Semiconductor Engineering, or a related discipline.
  • Candidates should have familiarity with data analysis, statistics, and data visualization techniques.
  • Programming experience in Python or a similar analytical programming language is preferred, but not strictly required.
  • Candidates should have an interest in semiconductor technologies, reliability engineering, or data-driven engineering applications.
  • Candidates should be curious and willing to explore Artificial Intelligence, Generative AI, AI Assistants, Agentic AI, Agentic Solutions, large language models, or other AI-enabled tools.
  • Candidates should be able to commit to a full-time internship period of six months.

Responsibilities

  • 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.
  • 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.
  • 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.
  • Complete a defined project plan outlining objectives, methodology, timeline, assumptions, and project risks.
  • Present a final technical presentation summarizing the project approach, analysis, findings, conclusions, and recommendations.
  • Document project outcomes and key learnings in a concise technical report.
  • Produce reproducible analysis artifacts, such as scripts, notebooks, workflows, or automation tools, with appropriate documentation.
  • Create knowledge-transfer documentation to support future learning and project continuity.

Desired Qualifications

  • Strong analytical, critical-thinking, and problem-solving abilities.
  • Effective written and verbal communication skills.
  • The ideal candidate should be pursuing a PhD in Electrical Engineering, Electronics Engineering, Materials Engineering, Applied Physics, Semiconductor Engineering, or a related discipline.

About the Company

Micron Technology

Makes memory and storage chips for AI and PCs

Micron Technology designs and manufactures memory and storage chips, mainly DRAM and NAND flash, used in data centers, PCs, phones, cars and industrial equipment. It is one of only three companies that make HBM, the stacked high-bandwidth memory placed beside processors in AI servers, and it is the largest memory chipmaker based in the United States. Unlike chip designers that outsource production, Micron runs its own fabs and assembly sites in the United States and across Asia. It earns money by selling chips, memory modules and solid-state drives to cloud providers, device makers and distributors. Micron was founded in 1978 and is headquartered in Boise, Idaho.

Company size
10,001+
Company stage
IPO
Headquarters
Boise, ID
Founded
1978

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