Intern - MFG PHOTO

Project Title

Internet of Things-Based Photolithography Equipment Monitoring and Anomaly Detection

Department

F10 Manufacturing, Photolithography

Project Description

The intern will undertake a structured engineering project focused on developing an Internet of Things-based solution for photolithography equipment and process monitoring.

Under the guidance of experienced engineers, the intern will study photolithography equipment behavior, process flow, and available sensor signals. The intern will apply Python programming, data analytics, system integration, and selected Machine Learning techniques to develop or enhance a defined monitoring use case.

The project will provide practical exposure to semiconductor manufacturing equipment, Internet of Things architecture, data ingestion, signal processing, visualization, and AI-Enabled anomaly detection. Project activities will be limited to the assigned use case and conducted with appropriate engineering guidance.

Objective of the Project

• Develop a strong understanding of photolithography equipment behavior, process flow, and process signals.
• Design and implement an Internet of Things-based solution for enhanced equipment or process monitoring.
• Enable earlier identification of equipment or process anomalies through data-driven and AI-Enabled methodologies.
• Build foundational skills in manufacturing analytics, system integration, and technical documentation.

Project Scope

• Study photolithography equipment architecture, process flow, and available sensor data for the assigned use case.
• Identify opportunities for Internet of Things integration within selected manufacturing equipment or engineering systems.
• Develop an end-to-end prototype encompassing data ingestion, processing, analysis, and visualization.
• Apply data filtering, optimization, analytics, and relevant Machine Learning techniques for anomaly detection.
• Contribute to one defined use case involving nozzle-camera imaging, temperature and humidity data, robotic acoustic signals, motor-driver data, or material-usage forecasting.

Learning Opportunities

• Gain exposure to advanced semiconductor manufacturing equipment and photolithography processes.
• Develop practical experience in Internet of Things architecture, sensor-data processing, and system integration.
• Apply data analytics, Machine Learning, and AI-Enabled techniques in a manufacturing environment.
• Collaborate with engineering and data science professionals while developing structured problem-solving and technical-documentation skills.

Deliverables

• Completion of one defined phase of an existing Internet of Things project or development of a new solution aligned with the project objectives.
• Demonstration of the proposed solution using relevant equipment, process, image, acoustic, environmental, or material-usage data.
• Documentation of the design approach, implementation methodology, analytical findings, limitations, and recommendations.
• A final technical report and presentation summarizing the project outcomes.

Impact of the Project

• Improve visibility into selected photolithography equipment or manufacturing-process signals.
• Enable earlier identification of abnormal equipment or process behavior and enhance equipment reliability.
• Provide findings that may inform future automation, analytics, and smart-manufacturing initiatives.

Skillsets Required

• Proficiency in Python programming, including exposure to Machine Learning or data-analytics libraries.
• Basic knowledge of electronics, sensors, controller-based systems, or industrial data acquisition.
• Familiarity with microcontroller platforms such as Arduino is advantageous.
• Familiarity with Artificial Intelligence, AI Assistants, or AI-Enabled workflows for data analysis and anomaly detection is advantageous.
• Strong analytical, problem-solving, communication, collaboration, and technical-documentation skills.

Course of Interest

The ideal candidate should be pursuing a degree or equivalent qualification in Internet of Things, Manufacturing Engineering, Semiconductor Engineering, Electrical Engineering, Computer Engineering, Data Analytics, or a related discipline.

Duration of Period

The ideal candidate should be able to commit to a full-time internship period of four to five months, equivalent to one full academic semester.

Opportunities for Full Time Employment

High-performing interns may be considered for future full-time employment opportunities, subject to business needs, position availability, and the applicable selection process.

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.

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.

Note: 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. 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.