Intern - PIE YE

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE LTD; Singapore; On-site; SGD 17,000 - 26,000; Full time

Job summary

Micron Technology, Inc. in Singapore seeks a diligent intern for Data Analytics for Yield Enhancement in Advanced Memory Manufacturing.

This full-time internship offers structured exposure to yield challenges, guided learning, and practical experience applying data analytics to understand yield behaviour using Python, multivariate analysis, and introductory machine learning. You will work with probe-test data, electrical failure modes, and fab metrics, develop an analytics tool, create

Qualifications

• Pursuing a degree in Electrical Engineering, Materials Science and Engineering, Data Science, Computer Engineering, or a related field.
• Strong interest in applying analytical methods to manufacturing data.
• Familiarity with Python-based data analysis, visualization, or ML concepts is advantageous.
• Willingness to learn new analytical methodologies and communicate technical findings clearly.

Responsibilities

• Develop a Python-based analytical solution for a defined yield-enhancement use case.
• Analyze probe-test data, electrical failure modes, and fabrication-process metrics.
• Apply multivariate data analysis techniques to identify patterns and opportunities for yield improvement.
• Prepare technical reports and visualizations of findings and recommendations.

Skills

Python programming

Data visualization

Machine learning basics

Analytical thinking

Education

Pursuing degree in Electrical Engineering or related analytics discipline

Tools

Python

Pandas

Job description

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

1 North Coast Drive, Singapore

Department

Product Integration Engineering, Yield Enhancement

Project Title

Data Analytics for Yield Enhancement in Advanced Memory Manufacturing

Project Description

This internship provides structured exposure to yield enhancement challenges in advanced memory manufacturing. Through guided learning and supervised technical exploration, the intern will gain practical experience applying data analytics techniques to understand yield behaviour and identify potential improvement opportunities.

The project will involve semiconductor probe-test data, electrical failure modes, fabrication-process metrics, multivariate analysis, Python-based analytics, and introductory Machine Learning techniques. The intern will also explore approved Artificial Intelligence and Generative AI tools to enhance data exploration, solution development, and technical documentation.

The project emphasizes learning, skills development, and the practical application of analytical methods in a manufacturing environment. It is designed to prepare the intern for future engineering and data-analysis roles in the semiconductor industry.

Objective of the Project

• Develop an understanding of yield behaviour in advanced memory devices.
• Analyze relationships among electrical failures, probe-test results, and fabrication-process metrics.
• Apply multivariate data analysis, Python, and introductory Machine Learning techniques to a defined yield-enhancement use case.
• Develop foundational skills in analytical problem-solving, engineering thinking, and technical communication.
  

Opportunities for Full-Time Employment

High-performing interns who demonstrate strong learning outcomes, technical curiosity, and professional growth may be considered for future internship or full-time employment opportunities, subject to business requirements, position availability, and the applicable selection process.

Project Scope

• Study semiconductor probe-testing principles, selected electrical failure modes, and relevant yield metrics.
• Analyze relationships among electrical failures, fabrication-process metrics, and inline-monitoring data.
• Apply multivariate data analysis techniques to identify patterns, correlations, and potential yield-improvement opportunities.
• Develop a Python-based analytical solution using relevant statistical, visualization, or introductory Machine Learning methods.
• Explore approved AI-Enabled or Generative AI workflows for data exploration, solution development, and documentation.
  

Learning Opportunities

• Build foundational knowledge of yield enhancement methodologies in advanced memory manufacturing.
• Develop analytical thinking using relevant manufacturing datasets.
• Gain practical experience with Python-based data analysis, visualization, and Machine Learning tools.
• Learn how Artificial Intelligence and Generative AI may be applied responsibly within an engineering workflow.
  

Deliverables

• A multivariate data analysis tool for the assigned yield-enhancement use case.
• A documented analysis of relevant probe-test, electrical-failure, fabrication-process, or inline-monitoring data.
• Visualizations and technical findings highlighting potential yield-improvement opportunities.
• A final technical report and presentation covering the methodology, results, limitations, and recommendations.
  

Impact of the Project

• Improve understanding of selected yield behaviour and electrical failure patterns.
• Enhance visibility into relationships among probe-test results, fabrication-process metrics, and inline-monitoring data.
• Identify potential yield-improvement opportunities through data-driven analysis.
• Demonstrate the value of analytical and AI-Enabled methods in advanced memory manufacturing.
  

Skillsets Required

• Basic understanding of data analysis, statistics, or engineering problem-solving.
• Familiarity with Python programming and an interest in applying analytical methods to manufacturing data.
• Familiarity with data visualization, Machine Learning, Artificial Intelligence, or Generative AI concepts is advantageous.
• Strong willingness to learn new analytical methodologies and communicate technical findings clearly.
  

Course of Interest

The ideal candidate should be pursuing a degree in Electrical Engineering, Materials Science and Engineering, Data Science, Computer Engineering, or a related engineering or analytics discipline.

Duration of Period

The ideal candidate should be able to commit to a full-time internship period of at least four months,.

About Micron Technology, Inc.

We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich lifefor 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 @micron.com

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.

Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.