Intern - PEE Diffusion (Process & Equipment Engineer), Singapore

F10 N and W Complementary Metal Oxide Semiconductor Matching and Wafer Edge Exclusion Optimisation Project

This internship project focuses on yield improvement through advanced process analysis and wafer edge performance optimisation within semiconductor manufacturing. The intern will examine matching behaviour between N and W process flows and evaluate wafer edge exclusion performance to reduce yield losses attributed to edge‑related effects. The project emphasises data‑driven analysis, defectivity characterisation, and inspection metric enhancement to enable sustained manufacturing performance.

The objective is to identify key contributors to process mismatch and wafer edge yield loss, and to develop analytical methodologies that strengthen yield performance and inspection accuracy in a production environment.

• Analyse inline, defect, and inspection data across modules to uncover root causes of yield variation.
• Evaluate bevel and wafer edge behaviour.
• Assess process sensitivity.
• Develop improved inspection algorithms that better represent true edge exclusion performance.

• Hands‑on exposure to semiconductor process integration.
• Yield analysis methodologies.
• Statistical data analysis.
• Defect inspection systems.
• Problem‑solving skills, engineering judgement, and teamwork with multi‑functional engineering team members.

• Close an estimated N and W yield gap of approximately 0.9%.
• Advance wafer edge exclusion targets towards zero non‑live dies at a defined edge exclusion width.
• Develop an improved wafer inspection algorithm that excludes known non‑process detractors while accurately reflecting edge performance.

The project contributes directly to improved yield stability, enhanced inspection accuracy, and stronger manufacturing decision‑making based on robust data insights.

• Analytical thinking.
• Semiconductor process knowledge.
• Statistical data analysis capability.
• Defectivity interpretation skills.
• Ability to translate data findings into engineering insights.

Microelectronics, Electrical Engineering, Chemical Engineering, Materials Science, Semiconductor Physics, or related engineering disciplines.

Minimum a semester‑long, full‑time internship of at least 5 months.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.