Diffusion Capacity Optimization Engineer Intern

Micron Technology; Singapore; On-site; SGD 17,000 - 22,000; Full time

Job summary

Micron Technology, Inc. in Singapore is offering a full-time internship to work on the Diffusion Capacity Optimization project.

You will analyze manufacturing data, evaluate workstation performance, and develop data-driven recommendations to improve equipment utilization, throughput, and cycle time. The role provides exposure to SPC, root-cause analysis, and AI-enabled analytics tools, with collaboration across Process, Equipment, Manufacturing, and Industrial Engineering teams.

Qualifications

• Strong analytical and problem-solving skills.
• Fundamental understanding of manufacturing or engineering systems.
• Familiarity with statistical analysis and data interpretation.
• Familiarity with Excel, JMP, Python, SQL, Power BI, or similar analytical tools is advantageous.
• Knowledge of Statistical Process Control (SPC), Lean Manufacturing, Root Cause Analysis, or AI-enabled analytics tools is advantageous.
• Strong communication and teamwork skills.

Responsibilities

• Analyze manufacturing data and identify bottlenecks.
• Evaluate workstation performance and capacity losses.
• Develop data-driven recommendations to improve throughput and cycle time.
• Collaborate with cross-functional teams and present findings.

Skills

Analytical skills

Problem solving

Manufacturing knowledge

Excel

JMP

Python

SQL

Power BI

SPC

Lean manufacturing

AI analytics tools

Communication

Teamwork

Education

Pursuing engineering degree

Tools

Excel

JMP

Python

SQL

Power BI

Job description

Micron Technology, Inc. in Singapore is offering a full-time internship to work on the Diffusion Capacity Optimization project.

You will analyze manufacturing data, evaluate workstation performance, and develop data-driven recommendations to improve equipment utilization, throughput, and cycle time. The role provides exposure to SPC, root-cause analysis, and AI-enabled analytics tools, with collaboration across Process, Equipment, Manufacturing, and Industrial Engineering teams.