NAND Cell Reliability Intern — Data Analysis & Automation

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE LTD; Singapore; On-site; SGD 17,000 - 28,000; Part time

Job summary

Micron Technology, Inc. invites PhD researchers to join as an intern focused on NAND reliability data analysis, variation learning, and automation. You will work with mentors and stakeholders to deliver a defined technical project with reproducible scripts and documentation.

Ideal candidates are pursuing a PhD in related fields, with strong analytical skills and communication abilities, ready to collaborate across TD and characterization teams.

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.

Responsibilities

• Work with mentors and stakeholders to deliver a focused technical project.
• Analyze reliability data and learn from variation sources relevant to NAND reliability.
• Develop or enhance scripts to improve repeatability and speed up analysis.
• Produce a final technical readout with method, results and recommendations.
• Create reproducible analysis artifacts and documentation for handoff.

Skills

Analytical thinking

Team collaboration

Effective communication

Python proficiency

Education

Pursuing PhD in Electrical/Electronics/Materials Engineering or Applied Physics

Tools

Python

Job description

Micron Technology, Inc. invites PhD researchers to join as an intern focused on NAND reliability data analysis, variation learning, and automation. You will work with mentors and stakeholders to deliver a defined technical project with reproducible scripts and documentation.

Ideal candidates are pursuing a PhD in related fields, with strong analytical skills and communication abilities, ready to collaborate across TD and characterization teams.