PhD Position in Intelligent Robotic Manufacturing Systems at University of Guelph
Explore intelligent robotic manufacturing systems integrating autonomous manipulation, AI, and digital twin technology. Collaborate with industry to produce next-gen smart factory platforms. Develop practical robotic applications for high-impact industries like automotive and aerospace.
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Project Description
Project Overview
The research centers on intelligent robotic manufacturing systems, an emerging field transforming production, assembly, and delivery processes. It involves integrating autonomous robotic perception and manipulation, human-robot collaboration, AI-powered adaptive manufacturing, and digital twin integration for real-time monitoring and optimization.
What You Will Do
The successful candidate will join a multidisciplinary team led by Dr. Sheng Yang, engaging in hands-on experimentation with physical robotic platforms and developing simulation environments. The role involves bridging academic research with industrial applications, fostering collaboration between academia and industry.
Expected Outcomes
This research aims to produce smart factory platforms that improve productivity, reduce costs, and enhance safety. The candidate will contribute to innovative solutions for sectors including automotive, aerospace, electronics, and consumer goods, with opportunities to publish and present at leading conferences.
Why This Matters
Industries worldwide seek automation solutions that increase flexibility and safety while lowering operational costs. By advancing intelligent robotic manufacturing, this research supports the global push toward smarter, more efficient factories responding fluidly to market demands.
Entry Requirements
How to Apply
Eligibility
Supervisor Profile
Dr. Sheng Yang leads research in intelligent robotic manufacturing systems, focusing on integrating AI with robotics for advanced manufacturing processes. His work includes autonomous robot perception and manipulation, human-robot collaboration, and digital twin integration. He is recognized for bridging academic research with industry applications in robotics and automation.