Intern - ADTS ATI Process Integration Engineer

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Project Title

NAND Structural Integration Analysis Using Inline Characterization

Project Description

This process integration internship provides structured training and practical experience in NAND semiconductor structural integration through inline characterization and data analysis.

The intern will analyze relationships among structural parameters, process performance, probe yield, and device operation. The project will provide exposure to real-world semiconductor manufacturing challenges, statistical analysis, process monitoring, cross-functional integration, and approved Artificial Intelligence-Enabled analytical workflows.

Objective of the Project

• Develop an understanding of NAND process integration flows, structural parameters, inline characterization, probe yield, and device operation.
• Analyze correlations between inline structural data, process performance, probe yield, and device behavior.
• Identify critical structural parameters and recommend appropriate inline monitoring specifications.
• Apply statistical and approved AI-Assisted analytical methods to improve data interpretation and engineering insight generation.

Opportunities for Full Time Employment

Interns may be considered for future internship or full-time employment opportunities based on business requirements, role availability, and the applicable recruitment process.

Project Scope

• Study the NAND process integration flow and identify key structural parameters relevant to process and device performance.
• Analyze inline characterization data and evaluate its relationship with process performance, probe yield, and device operation.
• Identify critical structural characteristics and define recommended inline monitoring specifications or control indicators.
• Collaborate with engineering subject matter experts from multiple process areas to understand cross-functional integration and validate analytical findings.

Learning Opportunities

• Gain practical exposure to NAND process integration, inline characterization, probe testing, yield analysis, and device-performance concepts.
• Learn to use statistical-analysis and visualization methods to identify correlations among structural, process, yield, and device data.
• Develop familiarity with JMP and approved AI-Assisted tools for data exploration, pattern identification, visualization, and technical documentation.
• Collaborate with cross-functional engineering teams and learn how analytical findings are translated into process-monitoring recommendations.

Deliverables

• A quantitative analysis of correlations between inline structural parameters, probe yield, and device performance.
• A documented proposal identifying key inline monitoring parameters and recommended specifications.
• A structured technical report covering the methodology, analytical results, validated AI-Assisted insights, findings, limitations, and recommendations.
• A final presentation communicating project outcomes, engineering impact, and potential future improvement opportunities.

Impact of the Project

• Improve understanding of the relationship between NAND structural parameters and device performance.
• Strengthen inline process monitoring and data-informed engineering decision-making.
• Identify opportunities to improve process control and probe-yield performance.
• Establish a structured analytical approach that may inform future NAND integration studies.

Skillsets Required

• Basic knowledge of semiconductor devices, manufacturing processes, or process integration.
• Strong analytical, structured problem-solving, data-interpretation, and technical communication skills.
• Familiarity with JMP, statistical analysis, data visualization, or equivalent analytical tools is preferred.
• Familiarity with approved Artificial Intelligence tools, AI Assistants, or AI-Enabled analytical workflows, including the ability to validate AI-generated outputs against engineering data.

Course of Interest

The ideal candidate should be pursuing a degree in Electrical Engineering, Electronic Engineering, Microelectronics, Materials Engineering, or a related field.

Duration of Period

The ideal candidate should be able to commit to a full time internship period of six months, from January 2027 to June 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 [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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