Intern - NAND Cell Reliability

Micron Technology, Inc; Singapore; On-site; SGD 11,160 - 27,900; Full time

Job summary

Micron Technology, Inc in Singapore is offering an internship focused on reliability data analysis and efficiency improvements in semiconductor technology. Interns will work closely with experienced mentors on a technical project involving data analysis, project planning, and delivering comprehensive documentation.

The ideal candidate will be pursuing a PhD in relevant fields and possess strong analytical skills. This role offers valuable experience in NAND memory reliability and collaboration within engineering teams.

Qualifications

• Currently pursuing a PhD in a relevant field.
• Basic understanding of semiconductor device physics and materials characterization.
• Strong analytical and problem-solving skills.

Responsibilities

• Analyze reliability datasets to understand sources of variation.
• Help track and interpret reliability indicators and error behaviors.
• Develop or enhance scripts to improve repeatability.

Skills

Analytical skills

Problem-solving skills

Collaboration

Communication skills

Education

PhD in Electrical/Electronics/Materials Engineering, Applied Physics, or related discipline

Job description

As an intern, you will work with an experienced mentor and project stakeholders to deliver a focused technical project. Depending on your background and business needs, your project may include work in one or more of the following areas:

Project Scope

• Reliability data analysis & variation learning: analyze reliability datasets to understand sources of variation (e.g., die/block/wordline effects), and communicate insights with clear visuals and summaries.
• Qualification learning support (intrinsic cell reliability): help track and interpret reliability indicators and error behaviors relevant to NAND reliability learning and qualification readiness.
• Automation / efficiency improvement: develop or enhance scripts to improve repeatability, reduce manual effort, and speed up analysis/learning cycles (Python preferred).

Expected Deliverables

• A well‑scoped project plan (problem statement, approach, timeline, risks)
• A final technical readout (slides + short write‑up) summarizing method, results, and recommendations
• Reproducible analysis artifacts (scripts/notebooks) and clear documentation for handoff

What You Will Learn

• How NAND memory reliability is evaluated, including key concepts like bit errors, error behavior, and reliability mechanisms under use conditions.
• How engineering teams use data to accelerate technology learning (including initiatives related to test time reduction, die‑level predictors, and efficiency improvements).
• How cross‑functional teams collaborate across TD, characterization, and (where applicable) system/validation partners.

Skillset Required

• Currently pursuing a PhD in Electrical/Electronics/Materials Engineering, Applied Physics, or a related discipline.
• Basic understanding of semiconductor device physics and materials characterization.
• Strong analytical and problem‑solving skills; demonstrated innovation is highly valued.
• Effective communication skills and a collaborative mindset.

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.