Intern - Photolithography Process Development

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 Fab10N, Singapore Department Process Development – Singapore (Photolithography) Project Title Edge Placement Error Modeling and Optimization Project Description This internship focuses on developing advanced modeling capabilities for photolithography process control in semiconductor manufacturing. The intern will gain exposure to photolithography patterning fundamentals and explore Artificial Intelligence and AI-enabled modeling approaches to enhance overlay accuracy and critical dimension uniformity. The role emphasises structured learning and project-based contribution through the development of data-driven models, including the application of Artificial Intelligence, AI-enabled analytics, and numerical modelling techniques . The intern will be guided through experimental data interpretation, model development, and deployment within a controlled process development environment. Objective of the Project To develop and optimise a predictive Edge Placement Error (EPE) model that enhances overlay and critical dimension uniformity control using advanced mathematical modelling and AI-enabled techniques. Opportunities for Full-Time Employment High-performing interns may be considered for future internship opportunities or full-time employment, subject to business needs and performance throughout the internship programme. Project Scope Develop mathematical and AI-enabled models for edge placement error prediction Analyse process data related to overlay and critical dimension uniformity Apply numerical methods and statistical techniques for process optimisation Explore integration of Artificial Intelligence (AI) or Generative AI-assisted workflows for modelling efficiency Conduct data validation using semiconductor characterisation techniques such as SEM and optical imaging Collaborate with engineers to refine modelling approaches and evaluate performance Learning Opportunities Introduction to photolithography in semiconductor manufacturing Hands-on exposure to process development methodologies Application of AI-enabled modelling and data analytics in real-world semiconductor challenges Understanding of overlay, critical dimension control, and process variability Experience with semiconductor metrology tools (SEM, optical imaging) Participation in structured internship engagements, learning activities, and project presentations Deliverables A validated Edge Placement Error (EPE) model for photolithography applications Documented methodology and modelling approach Analysis report on overlay and critical dimension improvements Final presentation to stakeholders summarising project outcomes and learnings Impact of the Project This project contributes to improved photolithography process accuracy and yield enhancement through better control of overlay and critical dimension uniformity, supporting advanced semiconductor manufacturing development. Skillsets Required Strong foundation in mathematical modelling and numerical analysis Programming knowledge (e.g., Python or similar tools) preferred Familiarity with AI-enabled tools, Artificial Intelligence concepts, or data analytics workflows is advantageous Analytical thinking and problem-solving skills Basic understanding of semiconductor processes or willingness to learn Course of Interest The ideal candidate should be pursuing Semiconductor Manufacturing, Nanomaterials, Physics, Mathematical Modelling, Programming, or related engineering disciplines. Duration of Period The ideal candidate should be able to commit to a full-time internship period of 4 to 6 months (minimum 4 months). 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. 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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