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Click here to search FindAPhD.com for PhD studentship opportunitiesAbout the Project
This PhD studentship, jointly funded by the UK Atomic Energy Authority and the University of Lincoln, falls within the framework of Robotics and Autonomous Systems (RAS) – one of the eight great technologies identified by the UK Government. The successful candidate will join the Lincoln Centre for Autonomous Systems (L-CAS), which is the University of Lincoln’s cross-disciplinary research group in robotics. L-CAS specialises in technologies for perception, learning, decision-making, control and interaction in autonomous systems, especially mobile robots and robotic manipulators, and the integration of these capabilities for multi-sector applications. The project will be carried out at the School of Engineering and in collaboration with the School of Computer Science.
Decommissioning fusion power plants are high-risk and tedious work that puts human operators’ lives at risk. Likewise, handling radioactive waste at decommissioning plants also poses risks to humans. Autonomous robots with manipulation capabilities are highly needed for remote sorting and segregating nuclear waste in addition to decommissioning operations. This PhD project aims to tackle the challenges in remote telemanipulation, design, and operational constraints of robots in fusion power plants. The PhD student will focus on introducing an innovative End-Over-End Walker (E-Walker) for decommissioning and maintenance operations in the nuclear fusion industry. The E-Walker is an omnidirectional walking robotic manipulator originally designed for in-space assembly and servicing missions.
The core objectives of this PhD research are:
1. Improve the kinematic and dynamic models of the E-Walker to assess its feasibility initially in ROS-based simulation environment.
2. In-line with the technical, operational and environmental requirements of JET as well as future nuclear fusion research and power plants such as ITER, STEP and EU-DEMO, re-validate the design of the E-Walker in simulation and design a standardized latching gripper mechanism for experimental verification of E-Walker’s mobility.
3. Develop novel algorithms for vision-based perception and a Machine Learning enabled path planning for autonomous navigation of the E-Walker (Data-driven self-learning robot).
4. Develop a novel robust control algorithm for collision-free navigation whilst avoiding joint singularities. Model-based control and Adaptive H-Infinity control are candidate architectures in addition to industry-standard PID control.
5. Verify and validate the algorithms developed for the E-Walker in simulation and experimentally using the test facilities at RACE. This is to evaluate the feasibility of the E-Walker for future decommissioning operations of JET and other Fusion remote maintenance applications.
6. Extended Objective – Develop a user (VR/AR) interface for Digital Twinning of the E-Walker to study anomalies and develop predictive measures to avoid significant errors during robotic decommissioning of JET.
The student will be primarily based at the University of Lincoln but will undertake research visits (up to 12 months) to RACE and test facilities in Cumbria.
Eligibility criteria
Applicants should have a First or Upper Second-class honours degree, ideally a master’s degree in Engineering (Robotics/Control/Electronics/Electrical/Mechanical/Mechatronics/Computer Science) and be able to demonstrate good problem-solving and analytical skills. Computing background in Matlab, Simulink, Python, ROS, C/C++ and SolidEdge will be an advantage. Applicants are expected to have good hands-on skills and excellent communication skills. Non-native speakers of English are expected to have an IELTS score of 6.5 or above (or equivalent TOEFL score) with no sub-test of less than 6.
How to apply
To formally apply for this studentship, you must submit the following:
(i) CV (2 pages),
(ii) Certified copies of degree certificates and transcripts,
(iii) Personal statement outlining your approach to the project and also explaining how your qualifications and experience meet the requirements (500 words),
(iv) Contact detail of two professional referees
(v) Proof of eligibility (e.g. Passport or Residence permit).
For initial screening, please email all the above documents directly to Prof Mini C. Rai ([Email Address Removed])
Shortlisted applicants will be contacted directly to arrange a suitable time for an interview. After that, only the successful candidate will need to apply via -
https://www.lincoln.ac.uk/home/course/egrphdrp/
This PhD studentship is expected to commence on 1st March 2023 or another mutually agreed start date. For any informal enquiries before applying, please get in touch with Prof Mini C. Rai ([Email Address Removed])
Supervisory Team
This studentship will be supervised by Prof Mini C. Rai (Primary academic supervisor), Prof Marc Hanheide (Co-Supervisor) and Robert Skilton (Industrial Supervisor from RACE).
About RACE and UKAEA
RACE (Remote Applications in Challenging Environments, http://www.race.ukaea.uk/) was founded in 2014 as part of the UK Atomic Energy Authority (UKAEA) fusion research and development programme - to create robots for operating in some of the most challenging environments imaginable. UKAEA’s wider mission is to lead the commercial development of fusion power and related technology, and position the UK as a leader in sustainable nuclear energy.
Based at Culham Science Centre near Oxford and at a new technology facility in South Yorkshire, UKAEA runs the UK’s fusion research programme and operates the Joint European Torus (JET) fusion experiment on behalf of scientists from 28 European countries. UKAEA is keeping the UK at the forefront of fusion as the world comes together to build the first powerplant-scale experiment, ITER – one step away from the realisation of nuclear fusion as a carbon-neutral energy source. JET serves as a test base for ITER, as well as future fusion demonstration powerplants putting electricity on the grid such as DEMO and UK’s own future STEP powerplant.
Application Deadline - Friday, 10th February 2023 (midnight GMT)
Funding Notes

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