About the RAINZ CDT
The EPSRC Centre for Doctoral Training in Robotics and Artificial Intelligence for Net Zero is a partnership between three of the UK’s leading universities (The University of Manchester, University of Glasgow and University of Oxford).
Robotics and Autonomous Systems (RAS) is an essential enabling technology for the Net Zero transition in the UK’s energy sector. However, significant technological and cultural barriers are limiting its effectiveness. Overcoming these barriers is a key target of this CDT. The CDT’s research projects will focus on how RAS can be used for the inspection, maintenance and repair of new infrastructure in renewables (wind, solar, geothermal, tidal, hydrogen) and nuclear (fission and fusion), and to support the decarbonization of existing maintenance and decommissioning of assets.
We are seeking motivated and curious graduate scientists and engineers who are interested in developing new skills and have a desire to help increase use of RAS to support the decarbonisation of the energy sector. RAINZ CDT students will play an important role in advancing this rapidly growing area of science and engineering.
Programme structure (1+3)*
Year 1 (Taught component): All students spend the first year at The University of Manchester undertaking taught MSc studies and bespoke CDT training. Students must achieve an average of 65% or higher in their MSc assessments to be considered for progression to the PhD component of the programme.
*Note: Students do not graduate with an MSc degree as the summer period is spent undertaking a CDT summer school rather than an MSc Dissertation.
Years 2 – 4 (PhD research): Students are based at the host institution to undertake their PhD research (i.e., either The University of Manchester, University of Glasgow, or University of Oxford), which will be complemented by a comprehensive cohort-wide training and employability programme.
The RAINZ CDT programme follows a cohort-based training and research designed to ensure that graduates are not only subject matter experts, but also equipped with highly valuable skills in teamwork, sustainability, EDIA and wellbeing, industrial engagement, and commercialisation. Each cohort tackles an industry co-created, cross-sector challenge that requires a multi-disciplinary team of engineers and scientists to solve it. Researchers explore different aspects of the challenge, which are then integrated through the RAINZ CDT annual research sprints. Find out more about the RAINZ CDT Training principles.
PhD Project Overview
Research Abstract: The project will focus on the teleoperation of autonomous ground vehicles (UGVs/AGVs) to enhance their functionality in constrained environments. While autonomous systems offer significant advancements, there are scenarios where human intervention via remote control is necessary. This research aims to develop a testbed for remotely controlling GVs, ensuring resilient and robust communication systems. Leveraging AI-driven solutions, the project will integrate energy-efficient, low-power AI techniques for real-time decision-making, contributing to the development of sustainable, autonomous operations. Subsequent experiments will investigate adversarial attacks and evaluate the resilience of these communications. A case study will explore the practical applications in industrial settings, particularly in manoeuvring fleets of autonomous trucks/robots within constrained environments.
Objectives
1. Develop a Teleoperation Testbed: Construct a comprehensive testbed for the remote control of UGVs, integrating necessary hardware and software components to enable effective teleoperation.
2. Ensure Communication Resilience: Conduct experiments to evaluate the resilience of communication channels. Design and implement innovative communication frameworks (e.g. task-oriented communications, secure communications) that ensure robust and resilient teleoperation under diverse conditions, including adversarial scenarios. The research will introduce new algorithms and protocols that proactively defend against communication failures and attacks.
3. Human-Machine Interaction: Study the interaction between human operators and autonomous systems to develop advanced approaches to optimize control interfaces and improve response times.
4. Conduct a Case Study in Industrial Settings: Explore the practical applications of teleoperated autonomous trucks/robots in industrial critical environments (e.g. NetZero asset management, maintenance, operation, etc.), focusing on their manoeuvrability within constrained spaces and the transition to autonomous operation in unconfined areas.
Eligibility
Applicants should hold a First or strong Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline. Applicants should also demonstrate evidence of programming experience.
Funding:
Successful applicants will be awarded a 4-year studentship covering:
· Tuition fees paid at Home student rate
· A tax-free stipend to help with living costs, set at the UKRI minimum rate* (i.e., £20,780 for 2025/26), which increases annually in line with inflation
· A Research Training and Support Grant to cover travel expenses and project consumables associated with your research including conference attendance, secondments, and other research and training activities
Additional funding is available to support a range of CDT activities, such as secondments or institutional visits, the purchase of additional specialised equipment, and an accessibility fund to support students with specific needs (e.g., caring responsibilities) when attending conferences or other required activities.
*TechExpert: As part of the UK Government’s TechFirst skills programme, successful Home applicants to Cohort 2 of the RAINZ CDT will receive a £10,000 per year enhancement to their UKRI minimum stipend.
Funding for this RAINZ CDT studentship is provided by the University of Glasgow.
How to Apply
Applications should be submitted through the RAINZ CDT website, where further information about the CDT is also available. Informal enquiries can be made by emailing rainz@manchester.ac.uk.
The deadline for submitting the RAINZ CDT application form is 5:00 pm, Friday 7 August 2026. Applications received after this deadline will not be considered.
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