AI-Driven Semiconductor Failure Analysis Intern

Micron Technology, Inc

Singapore

On-site

SGD 20,000 - 27,000

Full time

4 days ago
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Job summary

Micron Technology, Inc. in Singapore offers a full-time internship in AI-driven semiconductor failure analysis and laboratory digitalisation. The project focuses on applying data analytics, AI workflows, and automation to speed up failure investigations and improve knowledge access.

We expect hands-on learning, dashboards, and tooling that enhance decision-making for high-volume memory manufacturing. Ideal candidates pursue a Bachelor’s degree in Electrical/Electronics/Computer/Data Science or

Qualifications

  • Basic programming knowledge in Python and SQL.
  • Familiarity with data analytics, data visualization, and workflow development.
  • Interest in AI-enabled engineering applications and automation.
  • Strong analytical, problem-solving and collaboration skills.

Responsibilities

  • Develop an AI-enabled solution to improve failure analysis workflow efficiency.
  • Create dashboards, automation tools or knowledge-management solutions for lab processes.
  • Collaborate with Test Engineering to validate requirements and proposed solutions.
  • Present findings and recommendations to engineering stakeholders.

Skills

Python
SQL
Data analytics
Data visualization
Workflow development
Automation tools

Education

Bachelor’s degree in Electrical Engineering
Bachelor’s degree in Electronics Engineering
Bachelor’s degree in Computer Engineering
Bachelor’s degree in Computer Science
Bachelor’s degree in Data Science
Bachelor’s degree in AI/Artificial Intelligence

Tools

Microsoft Copilot

Job description

Micron Technology, Inc. in Singapore offers a full-time internship in AI-driven semiconductor failure analysis and laboratory digitalisation. The project focuses on applying data analytics, AI workflows, and automation to speed up failure investigations and improve knowledge access.

We expect hands-on learning, dashboards, and tooling that enhance decision-making for high-volume memory manufacturing. Ideal candidates pursue a Bachelor’s degree in Electrical/Electronics/Computer/Data Science or

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