Intern - Mfg Photo (IoT Photolithography Monitoring)

About the role

Micron is offering an internship in its F10 Manufacturing, Photolithography department. The project develops an Internet of Things-based solution for monitoring and anomaly detection of photolithography equipment and processes. Under the guidance of experienced engineers, the intern studies equipment behaviour, process flow and sensor signals, applying Python, data analytics, system integration and selected machine learning techniques. High-performing interns may be considered for future full-time employment.

Key responsibilities

• Study photolithography equipment architecture, process flow and available sensor data for the assigned use case.
• Identify opportunities for IoT integration within selected manufacturing equipment or engineering systems.
• Develop an end-to-end prototype covering data ingestion, processing, analysis and visualization.
• Apply data filtering, optimization, analytics and machine learning techniques for anomaly detection.
• Contribute to one defined use case such as nozzle-camera imaging, temperature and humidity data, robotic acoustic signals, motor-driver data or material-usage forecasting.
• Deliver a completed phase of an existing IoT project or a new solution, demonstrate it with relevant data, document the approach and findings, and present a final technical report.

Required profile

• Pursuing a degree or equivalent in IoT, Manufacturing Engineering, Semiconductor Engineering, Electrical Engineering, Computer Engineering, Data Analytics or a related field.
• Able to commit to a full-time internship of four to five months.
• Strong analytical, problem-solving, communication, collaboration and technical-documentation skills.

Required skills

• Proficiency in Python, 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 AI assistants or AI-enabled workflows for data analysis and anomaly detection is advantageous.