# Intern - Digital Automation & Solutions Team [Micron Technology](https://www.jorb.ai/firms/micron-technology.md) · Singapore · [Research / Applied Science](https://www.jorb.ai/jobs/research-applied-science.md) Micron Technology is hiring a Intern - Digital Automation & Solutions Team in Singapore. Posted 2026-08-13; applications close 2026-10-12. **Apply**: https://careers.micron.com/careers/job/43333524 Posted 5d ago. ## Role details ## Job Overview Join an inclusive team passionate about 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, while committing to integrity, sustainability, and giving back to our communities. ## Location, Department, and Project - **Location:** Singapore - **Department:** Digital Automation & Solutions Team - **Project Title:** Dynamic Batch Delivery Scheduling System for Autonomous Mobile Robot Fleet Operations ## Project Description Micron’s Fab 10 facility uses a fleet of Autonomous Mobile Robots to complete internal parts-delivery requests across the site. Currently, warehouse technicians determine whether multiple delivery requests should be grouped into a single robot mission or released individually, based on factors such as delivery priority, destination proximity, robot availability, and estimated return timing. This project focuses on developing a dynamic scheduling system that evaluates the full queue of pending delivery requests in real time. The system will determine whether a request should be grouped with other compatible requests, released immediately to the next available robot, or held briefly for a returning robot. The goal is to improve delivery scheduling decisions and reduce overall fleet-wide delivery time through data-driven optimization. ## Objective Design, develop, and validate a dynamic scheduling model that improves Autonomous Mobile Robot fleet utilization, reduces delivery waiting time, and enables more consistent decision-making for internal parts delivery. ## Project Scope - Study the current manual dispatching and delivery grouping process. - Identify relevant data inputs, operational constraints, and decision factors. - Formulate the scheduling and delivery grouping problem into an optimization model. - Develop and test a real-time scheduling algorithm. - Compare algorithm performance against current dispatching outcomes. - Document the methodology, results, and recommendations for future implementation. ## Learning Opportunities - Gain exposure to smart manufacturing and warehouse automation in a semiconductor environment. - Apply optimization, scheduling, routing, and data analysis concepts to a real business problem. - Learn how Autonomous Mobile Robot fleet operations are planned and evaluated. - Develop practical experience in modelling, algorithm development, simulation, and performance benchmarking. - Build stakeholder communication skills through project reviews and final presentation. - Gain exposure to Artificial Intelligence-enabled workflows, Generative Artificial Intelligence, Code Assist tools, and Large Language Models where relevant to research, analysis, documentation, and solution development. ## Deliverables - Current-state process and constraint analysis. - Optimization model for dynamic delivery scheduling and request grouping. - Prototype scheduling algorithm. - Performance comparison against current dispatching outcomes. - Final report with methodology, findings, results, and recommendations. - Final presentation to stakeholders. ## Impact This project is expected to improve the efficiency of Autonomous Mobile Robot fleet operations by enabling more consistent scheduling decisions, reducing delivery waiting time, and improving robot utilization. It may also provide a foundation for future automation, optimization, and smart manufacturing enhancements within internal logistics operations. ## Skillsets Required - Foundation in optimization, operations research, scheduling, routing, or combinatorial optimization. - Programming knowledge for modelling and analysis, preferably Python. - Strong analytical and problem-solving skills. - Ability to work with data, process flows, and operational constraints. - Good communication and documentation skills. - Familiarity with optimization solvers such as Gurobi or Google Operations Research Tools is preferred. - Familiarity with simulation, data analytics, Artificial Intelligence-enabled workflows, Generative Artificial Intelligence, Code Assist tools, or Large Language Models is preferred, where relevant to the project. ## Course of Interest The ideal candidate should be pursuing Industrial Engineering, Systems Engineering, Mechanical Engineering, Computer Engineering, Computer Science, Data Science, Operations Research, Supply Chain Engineering, or a related course of study. ## Internship Duration The ideal candidate should be able to commit to an internship period of 5 months. ## Opportunities for Full-Time Employment Successful completion of the internship may provide the candidate with opportunities to be considered for future full-time employment, subject to business needs and individual performance. ## Applying to this role This Intern - Digital Automation & Solutions Team role at Micron Technology runs through the firm's own careers portal and expects a CV and cover letter written specifically for the posting, not a portable submission carried across firms. Jorb AI's application agent tailors a CV and cover letter from your background to this posting and tracks the role alongside the rest of your applications. [Tailor this application](https://www.jorb.ai/signup?ref=job-atom&firm=micron-technology&job=6a7db532fa7cc17780344b95) ## More open roles at Micron Technology - [Engineer, MRDA Process](https://www.jorb.ai/jobs/6a82fb09c05296580022fa6a.md) – Singapore, posted 1d ago - [Intern - TEM Engineer](https://www.jorb.ai/jobs/6a7db532fa7cc17780344b91.md) – Singapore, posted 5d ago - [Intern- Test Solutions Engineer](https://www.jorb.ai/jobs/6a7db532fa7cc17780344b92.md) – Singapore, posted 5d ago - [Environmental Engineer Natural Resources](https://www.jorb.ai/jobs/6a7c9bc8a77717e27bf2118f.md) – New York, posted 6d ago - [Intern – Manufacturing Technician (Wet Process and Data Analysis)](https://www.jorb.ai/jobs/6a74427acc726f3ea03d5054.md) – Singapore, posted 12d ago ## Other open Research / Applied Science roles - [PhD Research Associate (Industry PhD Program) - Artificial Intelligence, SAP Labs Singapore](https://www.jorb.ai/jobs/69503ab2340e619957b1718c.md) at [SAP](https://www.jorb.ai/firms/sap.md) – Singapore, posted 7mo ago - [2027 Machine Learning Research Associate Program - PhD (New York)](https://www.jorb.ai/jobs/6a2c0d0370b3225d345daa2b.md) at [Morgan Stanley](https://www.jorb.ai/firms/morgan-stanley.md) – New York, posted 2mo ago - [PhD Research Scientist Intern - Reinforcement Learning for Diffusion Modelling](https://www.jorb.ai/jobs/6a7590fa25ecd425810a78c5.md) at [Canva](https://www.jorb.ai/firms/canva.md) – London, posted 10d ago - [PhD Student Intern - AI Research](https://www.jorb.ai/jobs/69cba3357cfd48bf87e17edf.md) at [SAP](https://www.jorb.ai/firms/sap.md) – Singapore, posted 4mo ago - [Research Scientist PhD Intern, 2027](https://www.jorb.ai/jobs/6a83309a44285d6a5998f4d5.md) at [Google](https://www.jorb.ai/firms/google.md) – London, posted 13h ago --- Updated: 2026-08-18 Canonical: https://www.jorb.ai/jobs/6a7db532fa7cc17780344b95