Intern - F10 ADTS ATE Dry Etch

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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 analysis and data visualization concepts.

• Willingness to learn and apply Artificial Intelligence, AI Assistants, or other AI-Enabled workflows to engineering analysis.
   

Course of Interest
The ideal candidate should be pursuing a Degree in Chemical Engineering, Electrical Engineering, Mechanical Engineering, Materials Engineering, Data Engineering, Computer Engineering, or a related field.

Duration of Period
The ideal candidate should be able to commit to a full time internship period of at least 5 months.

About Micron Technology, Inc.

We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience.

To learn more, please visit micron.com/careers

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.

To request assistance with the application process and/or for reasonable accommodations, please contact [email protected]

Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.

Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.

AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.   

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