Copper Sputter Process Intern - AI & Data Analytics

1100 Micron SemiAsiaOP Pte Ltd

Singapore

On-site

SGD 20,000 - 27,000

Full time

13 days ago
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Job summary

Micron Technology, Inc. in Singapore is offering a 4-month full-time internship in the HVM Engineering - Process and Equipment Engineering team.

You will support advanced copper sputter process development for next-generation metallization, leveraging AI and data analytics tools to derive actionable insights. Collaboration with cross-functional teams will help improve yield, reliability, and manufacturing readiness, with potential consideration for full-time employment based on performance.

Qualifications

  • Pursuing engineering degree in a related field.
  • Strong analytical and problem-solving abilities.
  • Experience with data analysis and statistics.
  • Familiarity with AI concepts and AI-enabled tools for data analytics.
  • Experience with programming or data analytics tools (Python, Power BI, SQL, JMP).
  • Good communication and teamwork skills.

Responsibilities

  • Assist process development and hardware qualification for copper sputter in HBM metallization.
  • Use AI tools and data analytics to identify performance trends.
  • Collaborate with cross-functional teams to improve manufacturing readiness.
  • Draft characterization and qualification reports.

Skills

Analytical skills
Data analytics
AI concepts
Python
Power BI
SQL
JMP
Communication skills
Teamwork

Education

Pursuing Chemical Engineering
Pursuing Electrical Engineering
Pursuing Materials Engineering

Tools

Python
Power BI
SQL
JMP

Job description

Micron Technology, Inc. in Singapore is offering a 4-month full-time internship in the HVM Engineering - Process and Equipment Engineering team.

You will support advanced copper sputter process development for next-generation metallization, leveraging AI and data analytics tools to derive actionable insights. Collaboration with cross-functional teams will help improve yield, reliability, and manufacturing readiness, with potential consideration for full-time employment based on performance.

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