Fully funded PhD Studentship in Data-Driven Hybrid Motion–Force Control for Robust Human–Manipulator Interaction at Lancaster University

Lancaster University – in collaboration with United Kingdom National Nuclear Laboratory (UKNNL)

We invite applications for a fully funded PhD studentship at Lancaster University’s School of Engineering, in partnership with United Kingdom National Nuclear Laboratory (UKNNL). This exciting project will develop novel data-driven, robust, and adaptive control methods for human–robot interaction and teleoperation, with direct applications in nuclear robotics, hazardous environment manipulation, and beyond.

Project Overview

Teleoperation is a critical enabler for safe and efficient operation in hazardous environments such as nuclear decommissioning. However, current industrial solutions suffer from limitations under uncertainty, time delays, and noisy sensing.

This PhD project will design and experimentally validate a hybrid motion–force control framework that ensures precise end-effector positioning while maintaining robust and adaptive force regulation under real-world conditions. Research will include:

• Development of nonlinear robust adaptive controllers and disturbance observers.
• Design of bilateral teleoperation schemes that enhance transparency and stability under communication delays.
• Integration of data-driven approaches for force estimation and safety.
• Experimental validation on industrial robotic platforms at the UKNNL Hot Robotics Facility.

The project provides the opportunity to work on cutting-edge robotics challenges with significant industrial impact, supported by state-of-the-art facilities at both Lancaster University and UKNNL.

Supervisory Team

• Dr Allahyar Montazeri (Lead Supervisor, School of Engineering, Lancaster University; Data Science Institute Member)
• Prof Plamen Angelov (Co-Supervisor, School of Computing and Communications, Lancaster University; Data Science Institute Member)

Training and Development

The successful candidate will receive a tailored training programme including:

• Hands-on training with ROS2, MATLAB/Simulink, and CoppeliaSim.
• Access to world-class robotics laboratories and facilities.
• Opportunities to engage with national and international conferences, workshops, and training events.
• Insight into the nuclear sector through industrial collaboration with UKNNL.

Eligibility

• Open to UK Home students only, due to clearance requirements for UKNNL facilities.
• Applicants should have (or expect to obtain) a First or Upper Second-Class degree (or equivalent) in Engineering, Control, Robotics, Computer Science, or a related discipline.
• Strong mathematical and programming skills (MATLAB, Python, or C++) are highly desirable.

Application Process

Applicants should submit:

1. A full CV.
2. A one-page cover letter outlining their motivation and suitability for the project.
3. Reference letter from two academics commenting on the candidate abilities.

Applications will be considered on a rolling basis until the position is filled, with an expected start date of January 2025.

For informal enquiries, please contact Dr Allahyar Montazeri (a.montazeri@lancaster.ac.uk).