Doctoral Researcher

Description:

The University of Sheffield’s Intelligent Manipulation Lab (IML), part of Sheffield Robotics, invites applications for a fully funded PhD studentship focusing on world models, predictive control, and foundation models for robotics. This research will push the boundaries of contact-rich robotic manipulation, combining tactile and vision sensing, model predictive control (MPC), reinforcement learning, and large-scale vision-language models.

The project aims to build action-conditioned predictors that can anticipate slip and deformation using high-rate tactile and visual feedback, enabling robust robotic control in sub-100 ms horizons. By integrating sampling-based MPC and reinforcement learning, the research will develop data-efficient and safe robotic behaviors under uncertainty. Furthermore, it will explore how foundation vision-language models can bridge high-level task descriptions with low-level control commands, targeting applications in grasping, non-prehensile manipulation, and deformable-object handling. Experiments will utilize robotic platforms such as Franka Emika and UR5 with advanced tactile skins.

About the Team and Institution

The University of Sheffield, a Russell Group university, is internationally recognized for excellence in robotics and AI. The Intelligent Manipulation Lab, led by Prof. Amir Ghalamzan, is at the forefront of innovation in tactile sensing, predictive control, and robot learning. The lab’s achievements include:

• Demonstrating a selective harvesting robot at COP26 (2021).

• Testing a strawberry-picking robot at Dyson’s Lincolnshire glasshouse.

• Publishing in Nature Machine Intelligence (2025).

• Collaborations with top universities (Oxford, Bristol, Imperial, Milan) and industrial partners in healthcare, manufacturing, and agri-food robotics.

Benefits of Joining the IML Team

• World-class facilities: Access to cutting-edge robotics platforms, high-resolution tactile sensing, and the Centre for Machine Intelligence (CMI).

• Collaborative environment: A diverse, multidisciplinary research community with postdocs, PhD students, and industry links.

• Global impact: Contribute to real-world robotics applications in agri-tech, healthcare, and decommissioning.

• Skill development: Hands-on expertise in ROS, Python, C++, reinforcement learning, MPC, and AI-driven robotics.

• Career growth: Opportunities to attend international workshops, conferences, and industry events, building both academic and professional reputation.

Candidate Requirements

• Bachelor’s degree (2:1 or above) and/or Master’s in Robotics, Electrical/Electronic Engineering, Computer Science, Mechanical Engineering, or related disciplines.

• Strong mathematical foundation and programming skills (Python, C++).

• Knowledge of machine learning, control systems, reinforcement learning, or AI.

• Desirable: Hands-on experience with ROS, tactile/vision-based sensing, MPC, reinforcement learning, or prior robotics research.