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Transportation of nuclear material at Sellafield Ltd faces a critical scalability challenge, requiring operations to increase from monthly to daily while maintaining safety standards. Sellafield’s successful deployment of their first autonomous heavy goods vehicle (HGV) proved technical feasibility in nuclear environments, but current operations require multiple safety operators (acting remotely or in-vehicle), making them unsuitable for scaling-up. The fundamental bottleneck for existing systems is inappropriate levels of trust between operators and autonomous systems; operators may either under-trust or over-trust.
This PhD will aim to develop comprehensive trust models for human-autonomous vehicle (AV) collaboration and then create adaptive systems that calibrate operator trust appropriately while enabling operator confidence in the autonomous decision-making and reduce cognitive workload.
This will enable single operators to supervise multiple AVs simultaneously. The research will use and adapt Sellafield’s existing proof of concept and collaborate with Digital Concepts Engineering Ltd (DCE) to create and test various human machine interface designs that optimize operator confidence and decision-making effectiveness rather than developing entirely new platforms.
This research will support the Nuclear Decommissioning Authority’s (NDA) long-term decommissioning mission while developing transferable expertise in autonomous system supervision across safety-critical nuclear environments.
This PhD includes a six-month secondment at Sellafield Ltd with the Special Nuclear Material (SNM) Innovation Team which will provide direct operational access to facilitate understanding of nuclear facility day-to-day operations. This will ensure that the research remains grounded in the nuclear environment realities while building essential industry relationships.
If you have any questions about the studentship, please email Dr Amina Hamoud at amina.hamoud@uwe.ac.uk.
Funding
This fully-funded (NDA bursary) studentship is available from 1 October 2026 for a period of three and a half years, subject to satisfactory progress and includes a tax-exempt stipend, which is currently £20,780 (2025/26) per annum.
In addition, full-time tuition fees will be covered for up to three and a half years (Home/UK only).
This studentship includes a generous research training support package, and will cover the accommodation for the Sellafield six-month secondment. In addition, UK National Nuclear Laboratory (UKNNL), Sellafield Ltd and Digital Concepts Engineering Ltd (DCE) will provide significant support including access to operational autonomous vehicle platforms, operator teams, and regulatory expertise when needed.
Eligibility
Applicants must have (or be on track to obtain) a first-class or upper second-class honours degree (2.1) or a distinction/merit at master’s level in Robotics, Computer Science or a related field. You will be curious, motivated by real-world impact, and comfortable working across academic and industrial environments.
Experience or strong interest in one or more of the following is particularly welcome:
- autonomous vehicles or autonomous systems more broadly
- human–computer interaction
- safety-critical systems.
How to apply
Please submit your application online. When prompted use the reference number 2627-OCT-CATE21.
Application deadline
The closing date for applications is 3 June 2026.
Supporting documentation
You will need to upload your research proposal, all your degree certificates and transcripts.
You will need to provide details of two referees as part of your application.
Interview dates
It is expected that interviews will take place in mid-June. If you have not heard from us by the end of June, we thank you for your application but on this occasion you have not been successful.
