Intern - Process & Equipment Engineer (Diffusion)

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Project Title Enhancing Poly-SiGe Gap Fill Performance in High Aspect Ratio Structures for Improved Die Strength and Reduced Wafer/Dice Bending

Project Description This project aims to improve Poly-SiGe gap filling in high aspect ratio (HAR) structures to enhance die strength and reduce block bending. The intern will study the impact of deposition conditions on film growth, conformality, and void formation, identify strategies to improve fill performance while minimizing early pinch-off, and correlate gap-fill characteristics with mechanical integrity.

The outcome will be a deeper understanding of the key mechanisms governing successful HAR feature filling and die-strength improvement.

Project Scope

• Investigate effects of process parameters on fill depth and gap-fill in HAR structure

• Identify process conditions that improve bottom-up fill while maintaining open feature entrances.

• Identify critical fill characteristics that contribute most to structural robustness.

• Recommend optimized window and qualification plan

Learning Opportunities

• Gain hands-on application on material science and semiconductor integration.

• Experience the end-to-end development cycle from problem definition to qualification proposal

• Collaborate with cross-functional engineering teams and subject matter experts.

Deliverables

• Quantitative comparison of voids, seams, and pinch-off behavior

• DOE and experimental matrix with SEM/TEM cross-section analysis of filled structures.

• Correlation between fill quality and die-strength/block-bending performance to recommend process window

Impact of Project

• Enhances die strength and reduces block bending through improved feature-fill quality and stress management.

• Provides a scalable process solution that can improve yield, reliability, and manufacturability for future technology nodes.

Skillsets Required

• Strong analytical and problem-solving skills.

• Familiarity with machine learning, statistical analysis, and AI-enabled workflows

• Familiarity with semiconductor materials, thin-film deposition, process integration, or materials characterization.

• Familiarity with Design of Experiments, statistical analysis, and interpretation of experimental data

Course of Interest: The ideal candidate should be currently pursuing a degree in Engineering, or a related field.

Duration: The ideal candidate should be able to commit to a full-time internship period of at least 5 months from Jan to Jun 2027.

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 hrsupport_sg@micron.com

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