AI-Driven Dry Etch Analytics Intern

Micron

Singapore

On-site

SGD 13,000 - 20,000

Full time

7 days ago
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Job summary

Micron Technology, Inc. in Singapore is offering a full-time internship in Dry Etch Process Performance Optimization using Data Analytics and AI. You will work with manufacturing and equipment data to analyze process stability, productivity, and yield, and develop data-driven improvement recommendations.

The ideal candidate is pursuing a Degree in Engineering or Data Engineering and has experience with Python, SQL, JMP, or Excel for data analysis and visualization. Duration: at least 5 months.

Qualifications

  • Strong analytical thinking and structured problem-solving skills.
  • Interest in semiconductor manufacturing, dry etch technology, or process engineering.
  • Basic experience with Python, SQL, JMP, Excel, or visualization tools.
  • Familiarity with statistical analysis and data visualization concepts.
  • Willingness to learn AI-enabled workflows in engineering analysis.

Responsibilities

  • Analyze dry etch process and equipment performance using manufacturing data.
  • Identify sources of process variation, performance drift, productivity loss, and yield impact.
  • Develop data-driven recommendations for improving process stability and equipment performance.
  • Explore AI-enabled approaches for faster pattern identification and engineering insight generation.

Skills

Python
SQL
Data analysis
Statistical analysis
Data visualization
Problem solving

Education

Engineering degree

Tools

JMP
Excel

Job description

Micron Technology, Inc. in Singapore is offering a full-time internship in Dry Etch Process Performance Optimization using Data Analytics and AI. You will work with manufacturing and equipment data to analyze process stability, productivity, and yield, and develop data-driven improvement recommendations.

The ideal candidate is pursuing a Degree in Engineering or Data Engineering and has experience with Python, SQL, JMP, or Excel for data analysis and visualization. Duration: at least 5 months.

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