Intern – Dry Etch Process and Equipment

Project Title

Dry Etch Process Optimization and Characterization

Location

Singapore

Department

Process Engineering – Dry Etch

Project Description

This internship project offers hands-on exposure to semiconductor dry etch process and equipment development within a manufacturing environment. The intern will participate in structured experimental studies to evaluate opportunities for improving process efficiency, reducing material cost, and minimizing process variation through data-driven analysis.

The intern will develop foundational knowledge of dry etch processes, process characterization techniques, and equipment fundamentals while gaining experience in analyzing engineering data to drive process improvements. Exposure to AI-enabled analytical tools may be provided to enhance data interpretation and engineering decision-making.

Objective of the Project

• Evaluate opportunities for process time reduction, material cost optimization, and process variation reduction through designed experiments.
• Build foundational knowledge of dry etch process principles and equipment fundamentals.
• Understand the relationship between key process parameters and product patterning outcomes.
• Develop problem-solving and data analysis skills applicable to semiconductor manufacturing.

Project Scope

• Learn the fundamentals of dry etch processes and associated hardware systems.
• Gain exposure to a dry etch application utilized in Micron manufacturing.
• Understand process and equipment characterization techniques and how process parameters influence patterning performance on product wafers.
• Design and execute structured experiments to evaluate process performance.
• Analyze experimental data to identify opportunities related to process efficiency, cost optimization, and variation reduction.
• Present engineering findings and recommendations based on experimental results.

Learning Opportunities

• Semiconductor manufacturing fundamentals.
• Dry etch process and equipment technology.
• Process characterization and optimization methodologies.
• Experimental design and statistical analysis techniques.
• Engineering problem-solving and technical communication.
• Cross-functional collaboration within a manufacturing environment.

Deliverables

• Optimization proposal for an existing dry etch process with measurable improvements in process time, material cost, and/or process variation.
• Technical analysis of experimental results and key process drivers.
• Technical presentation summarizing the experimental approach, analysis, recommendations, and key findings.

Impact of the Project

The project contributes to continuous improvement initiatives by identifying opportunities to enhance process efficiency, improve manufacturing consistency, and reduce operating costs through engineering analysis and process optimization.

Skillsets Required

• Good communication and presentation skills.
• Ability to work effectively in a team environment.
• Strong analytical and problem-solving skills.
• Strong interest in learning and applying engineering fundamentals.
• Familiarity with data analysis tools and basic AI-enabled analytical workflows is advantageous.

Course of Interest

The ideal candidate should be pursuing a Degree in Engineering, Physical Sciences, Statistics, Data Analytics, Materials Science, Chemical Engineering, Electrical Engineering, Mechanical Engineering, or a related discipline.

Duration of Period

The ideal candidate should be able to commit to a full-time internship period of 6 months from January 2027 onwards.