Intern - F10 Process Integration Analytics at Micron Technology in Singapore, Singapore

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.
• AI-Enabled Inline Health Monitoring and Process Drift Detection
• This internship project focuses on developing and enhancing an inline health-monitoring system for Process Integration. Through close mentorship and hands-on learning, the intern will extract and organize relevant inline metrics, targets, and specifications, and develop visualizations for process-health monitoring.
• The intern will gain exposure to semiconductor Process Integration by analyzing process data and exploring Micron-qualified Artificial Intelligence tools. The project will also evaluate opportunities to automate selected parts of the inline monitoring workflow, improve drift detection, and enhance engineering
• productivity.
• Objective of the Project
• Develop an AI-Enabled inline health-monitoring and process drift-detection solution.
• Improve the visualization of inline metrics, targets, specifications, and process-health trends.
• Explore Artificial Intelligence applications for process-window optimization and engineering workflow automation.
• Establish a reusable solution that can be further developed after the internship.
• High-performing interns who demonstrate strong technical capability, learning agility, and successful project outcomes may be considered for future internship or full-time employment opportunities, subject to business needs and hiring requirements.
• Gain practical exposure to semiconductor Process Integration and inline process control.
• Develop skills in data extraction, statistical analysis, visualization, and process drift detection.
• Learn how process metrics, targets, and specifications are used to evaluate manufacturing health.
• Explore Artificial Intelligence, AI Assistants, and Agentic AI solutions for engineering productivity and process optimization.
• Collaborate with experienced engineers and learn structured approaches to process monitoring and excursion response.
• An enhanced inline health-monitoring solution with data extraction, visualization, and alerting capabilities.
• A proof-of-concept Artificial Intelligence integration for automated inline monitoring or process optimization.
• An AI Agent prototype for selected Process Integration workflow activities.
• A handover package containing relevant documentation, findings, and recommendations for continued development or expansion.
• Impact of the Project
• Improve visibility into inline process health and potential performance drift.
• Enable faster identification of process deviations and excursion risks.
• Enhance engineering productivity through AI-Enabled analysis and workflow automation.
• Provide the intern with real-world exposure to semiconductor Process Integration and data-driven process control.

Responsibilities

• Extract, organize, and validate inline metrics used for process-health monitoring.
• Develop an AI-Enabled dashboard for inline monitoring, visualization, and process drift detection.
• Explore Micron-qualified Artificial Intelligence tools for drift detection and process-window optimization.
• Develop an AI Agent proof of concept for selected Process Integration activities, such as data collection, lot funding, and experiment-summary generation.

Requirements

• Strong problem-solving mindset with data-analysis capabilities, including statistics, visualization, and large dataset interpretation.
• Familiarity with programming, data analytics, dashboard development, or automation tools is advantageous.
• Good communication and cross-functional collaboration skills.
• Interest in semiconductor manufacturing, Process Integration, and process control.
• Familiarity with Artificial Intelligence tools, AI Assistants, Agentic AI, or AI-Enabled workflows is advantageous.
• The ideal candidate should be pursuing a Degree in Engineering, Statistics, Mathematics, Computer Science, Materials Science, Physics, or a related field.
• The ideal candidate should be able to commit to a full time internship period of at least 5 months, from January 2027 to June 2027.

Skills

Required

• Strong problem-solving mindset