Intern - F10 ADTS ATE Dry Etch

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location Singapore Department Advanced Device Technology and Systems, Advanced Technology Enablement Dry Etch, F10 Project Title Dry Etch Process Performance Optimization Using Data Analytics and Artificial Intelligence Project Description Dry etch is a critical semiconductor manufacturing process that has a significant impact on product yield, cycle time, and manufacturing capacity. This internship project focuses on applying process engineering, data analytics, and AI-Enabled methods to understand process behavior, identify performance gaps, and develop improvement recommendations. The intern will work with manufacturing, equipment, and process datasets to explore opportunities related to process stability, productivity, and yield. The project will provide practical exposure to dry etch process engineering, industrial data analytics, data visualization, and Artificial Intelligence applications. Objective of the Project 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. Opportunities for Full Time Employment High-performing interns who demonstrate strong technical capability, learning agility, and successful project outcomes may be considered for future internship or full-time employment opportunities, subject to business needs and hiring requirements. Project Scope Analyze Statistical Process Control, equipment performance, utilization, and fault data to identify trends and performance gaps. Evaluate potential process, recipe, hardware, or control improvements using data-driven methodologies. Correlate process, inline measurement, metrology, and equipment data where applicable. Develop dashboards or scripts for data visualization, monitoring, and AI-Enabled insight generation. Learning Opportunities Gain practical exposure to dry etch processes and semiconductor manufacturing systems. Develop experience in process characterization, statistical analysis, and manufacturing data interpretation. Learn to use Python, Structured Query Language, JMP, Excel, or visualization tools for engineering analysis. Explore the application of Artificial Intelligence and AI Assistants for pattern recognition, data summarization, and engineering productivity. Collaborate with process and equipment engineers to translate analytical findings into improvement recommendations. Deliverables Data-driven analysis of key dry etch process and equipment performance metrics. Clearly defined performance gaps with relevant data and supporting evidence. Recommendations for process, equipment, or monitoring improvements. Final presentation and project documentation summarizing the methodology, findings, and recommendations. Impact of the Project Improve understanding of dry etch process stability and productivity. Enable faster identification of process and equipment performance gaps. Enhance data-driven decision-making within F10 Dry Etch operations. Skillsets Required Strong analytical thinking and structured problem-solving skills. Interest in semiconductor manufacturing, dry etch technology, or process engineering. Basic experience with Python, Structured Query Language, JMP, Excel, or similar data-analysis tools. Familiarity with statistical analysi