Sheng Yang

Funded PhD/MASc opportunity at the University of Guelph in autonomous drone systems for precision agriculture . The project sits at the intersection of Robotics , Artificial Intelligence , Autonomous Systems , UAV Technologies , and Agriculture , with a focus on UAV control and system integration . The successful student will contribute to cutting-edge research supporting sustainable agriculture through drone-based sensing, control, and autonomous operation. Supervisor/announcer: Sheng Yang, Associate Professor at the University of Guelph. Eligibility highlights: applicants should come from Computer Engineering, Electrical Engineering, Mechatronics, Robotics, or a related field. Preferred experience includes drone flight control, robotics, autonomous systems, ROS, and UAV platforms such as PX4 or ArduPilot. Strong hands-on UAV hardware development experience is required. A minimum GPA of 85% (or equivalent) is expected, along with at least one first-authored journal/conference publication or an equivalent patent. Exceptional MASc applicants with strong relevant experience are also encouraged to apply. Funding: the position is described as funded, but no stipend, tuition, or other financial details are listed. Application: submit a single PDF containing a cover letter, CV, academic transcripts (unofficial copies accepted), and one representative publication if available. Applications are reviewed on a rolling basis until the position is filled. Start dates: September 2026 for domestic students, January 2027 for international students, with flexible start dates possible thereafter.

Funded PhD opportunity at the University of Guelph in intelligent robotic manufacturing systems . The project sits at the intersection of robotics , artificial intelligence , advanced manufacturing , industrial automation , and digital twins , with a strong emphasis on real-world deployment in manufacturing settings. The research will explore autonomous robotic manipulation and perception, AI-driven decision-making for adaptive manufacturing, human-robot collaboration in industrial environments, and integration with smart factory systems. Both physical robotic platforms and simulation environments will be used, making this a strong fit for candidates interested in applied robotics and intelligent systems research. Preferred applicants should have an engineering background, ideally in Mechanical, Mechatronics, Electrical, or Manufacturing Engineering, plus a Master’s degree in Robotics, Mechanical/Mechatronics Engineering, Artificial Intelligence, or Intelligent Systems. The post also asks for strong experience with robotics/control/automation, hands-on work with ROS/ROS2, robotic arms and sensors, and programming in Python and/or C++. Familiarity with robot perception, learning-based control, simulation, digital twin technologies, or industrial automation is an advantage. Academic expectations include strong grades (85%+, 17/20, or 8/10 GPA equivalent), at least one first-author publication, independent and collaborative working ability, and strong English communication skills. The position is funded and expected to start in Fall 2026 (flexible), with applications reviewed on a rolling basis until filled. To apply, email a single PDF to Dr. Sheng Yang at [email protected] including a CV, transcripts, statement of research interests and relevant experience, one representative publication, and two referees’ contact details.

The University of Guelph in Ontario, Canada, is offering a funded postdoctoral position in the area of Industrial Human-AI Collaboration, with a focus on next-generation smart manufacturing systems. The successful candidate will join a research project led by Dr. Sheng Yang, Associate Professor at the University of Guelph, and will work on topics including human-robot and AI collaboration, deep learning (such as transformers, transfer learning, multimodal models, Sim2Real), and the development and simulation of robotic systems using tools like ROS2 and Python. Applicants should have a PhD in Robotics, AI, Computer Science, Smart Manufacturing, or a related field, obtained within the last five years or to be granted before September 2026. A strong research record is required, including at least three first-authored Q1 publications. Candidates should also have hands-on experience in robotic systems and simulation, as well as experience in intelligent systems, automation, or manufacturing. Project and team management experience is considered an asset. The position is fully funded, though specific details about the stipend or salary are not provided. The research group is looking for candidates who are passionate about advancing the field of human-AI collaboration in industrial settings and who can contribute to both the theoretical and practical aspects of the project. To apply, candidates should email a single PDF containing a cover letter, CV, academic transcripts (unofficial copies are acceptable), one representative publication, and a Google Scholar profile link to Dr. Sheng Yang at [email protected]. The subject line should read 'Postdoc Position in Industrial Human-AI Collaboration'. Applications will be reviewed on a rolling basis until the position is filled, and only shortlisted candidates will be contacted. For more information about Dr. Sheng Yang, visit his LinkedIn profile . The University of Guelph is a leading Canadian institution known for its research in engineering, computer science, and smart manufacturing.

A fully funded PhD position is available at the University of Guelph in the Design Innovation and Intelligent Manufacturing (DIIM) Lab, supervised by Associate Professor Sheng Yang. The research focuses on knowledge representation and learning for smart agriculture, working at the intersection of artificial intelligence, knowledge modeling, deep learning (especially graph-based learning), and digital farming systems. The ideal candidate will have a background in software engineering, computer engineering, computer science, or information technology, with strong programming skills and research experience in information retrieval, knowledge modeling, and deep learning. Knowledge of app development is considered an asset. Applicants must submit a CV, transcripts of all studies, and a sample publication. The position is fully funded, with a flexible start date as early as possible or by January 2026. For more information or to apply, contact Dr. Sheng Yang at [email protected].