Intern - NAND Cell Reliability

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 10,155 - 12,164; Full time

Job summary

1100 Micron SemiAsiaOP Pte Ltd in Singapore offers an internship focused on reliability data analysis related to NAND memory. Interns will work closely with experienced mentors on technical projects, enhancing their analytical skills and understanding of semiconductor physics.

Key responsibilities include analyzing reliability datasets, automation of processes through Python, and developing comprehensive project plans. Candidates must be pursuing a PhD in a relevant field. An opportunity to learn and innovate in a collaborative environment is provided.

Qualifications

• Currently pursuing a PhD in a relevant engineering discipline.
• Basic understanding of semiconductor device physics and materials characterization.
• Demonstrated innovation in problem-solving.

Responsibilities

• Analyze reliability datasets to understand sources of variation.
• Track and interpret reliability indicators for NAND reliability.
• Develop scripts to improve analysis and learning cycles.

Skills

Analytical skills

Problem-solving

Communication skills

Collaborative mindset

Education

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

Tools

Python

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 our 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 fuels the very innovation we are pursuing.

Internship Overview

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:

• 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

Learning Objectives

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); and how cross‑functional teams collaborate across TD, characterization, and (where applicable) system/validation partners.

Qualifications

• 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.

Equal Employment Opportunity

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.