AI-Driven AMHS Intern: Optimize Cross-Fab Transport

Micron Technology, Inc.

Singapore

On-site

SGD 17,000 - 22,000

Full time

14 days+

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Job summary

Micron Technology Singapore is offering a 6-month full-time internship focused on data-driven optimization of Automated Material Handling System (AMHS) in a high-volume semiconductor fab. You will analyze historical movement data, apply AI methods, and explore optimization opportunities to reduce non-value-added transfers.

The project exposes you to semiconductor manufacturing operations, logistics optimization, and data analytics while collaborating with cross-functional teams.

Qualifications

  • Pursuing CS/DS/AI/Engineering with interest in data analytics.
  • Proficiency in Python/SQL or data analytics tools.
  • Familiarity with AI, Generative AI, AI assistants or AI workflows.
  • Knowledge of statistics, visualization or modelling techniques.

Responsibilities

  • Analyze cross-fab AMHS transportation data and movement patterns.
  • Apply AI Assistants and AI-enabled analytical methods to uncover drivers.
  • Evaluate factors like tool distribution, scheduling, staging, test wafer moves, empty FOUP transfers.
  • Develop and assess optimization concepts using data analysis, modelling or simulation.
  • Generate recommendations to improve transport efficiency and reduce non-value-added movements.
  • Present findings and opportunities to project stakeholders.

Skills

Python
SQL
Data analytics tools
Analytical skills
Problem-solving
Communication

Education

Pursuing Computer Science / Data Science / Artificial Intelligence / Engineering

Tools

AI Assistants

Job description

Micron Technology Singapore is offering a 6-month full-time internship focused on data-driven optimization of Automated Material Handling System (AMHS) in a high-volume semiconductor fab. You will analyze historical movement data, apply AI methods, and explore optimization opportunities to reduce non-value-added transfers.

The project exposes you to semiconductor manufacturing operations, logistics optimization, and data analytics while collaborating with cross-functional teams.

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