About the Project
How do we build and maintain trustworthy-by-design digital twins for nuclear manufacturing environments, with integrated VVUQ, assumption management and twin-drift monitoring?
- Lead Supervisor: TBC (JC Chaplin) University of Nottingham
- Second Supervisor: To be confirmed
- Industry Partner: Sought
- Project Start: October 2026
- Target Background: Mechanical Engineering, Digital Manufacturing, possibly Computer Science
- Industrial Funding: Sought
- Advert Close Date: TBC
- Programme: 4 year Engineering Doctorate (EngD) with industry placement
Digital twins you can rely on for decades.
Digital twins (DTs) are increasingly used to improve monitoring, prediction and optimisation. In safety-critical settings such as nuclear manufacturing, the value of the DT relies on its fidelity and trustworthiness: how closely it matches the physical twin, and how much its insights can be relied upon.
This challenge is more significant when the DT operates over long periods, where the manufacturing system may undergo equipment upgrades, process changes and evolving requirements. DTs must therefore have a plan covering verification, validation and uncertainty qualification (VVUQ) over time.
Applying a comparable level of rigour to a nuclear manufacturing process would allow a credible twin that offers reliable insights, reducing build time and facilitating auditing and record keeping.
Aims and objectives
Aim: how do we build and maintain trustworthy-by-design digital twins for nuclear manufacturing, integrating VVUQ, assumption and uncertainty management, and monitoring drift over time?
Objectives:
- Digital twin credibility assessment: how much VVUQ does a twin need for the intended use and risk, and how is it monitored as the model evolves?
- Lifecycle governance: how are assumptions, limits, data provenance and context of use recorded and preserved over time?
- Twin drift: how do we formalise and automate synchronisation, and understand the trade-off between frequent and infrequent synchronisation?
- AI for digital twins: how far must VVUQ extend into any AI used to build or synchronise the twin?
- Quantifying trust and efficacy: what KPIs measure fidelity and trustworthiness?
Alignment to STAND-UP impact targets
- >50% reduction in overall build or decommissioning process time
- >40% reduction in maintenance time (not applicable)
- >30% reduction in person hours on builds
Apply for this project
Contact the lead supervisor or programme team to discuss your interest. Full application instructions are on the How to Apply page.
Funding Notes
£26,000 per year, plus a significant project, travel and training budget. Open to UK home students.
Where will I study?
University of Nottingham
Ranked among the UK’s top 20 universities and in the world’s top 100 (QS World University Rankings 2026), Nottingham offers a PhD experience that combines research excellence with real-world impact. You’ll be taught by academics who are experts in their field, at a university known for its pioneering research – from the birthplace of the MRI scanner to Nobel Prize-winning discoveries.
For the fifth year running, more of our graduates are in highly skilled employment than any other UK university (HESA Graduate Outcomes 2021–2025). With careers support for life and strong employer links, we’ll help you build a future without limits.
Nottingham is the third most targeted UK university by leading graduate employers (High Fliers 2024), with global connections to companies like JP Morgan, ASOS, Unilever, GSK, and Deloitte.
Ranked in the top 10 for student life (UniCompare 2026), our award-winning campuses are home to students from over 150 countries. With an amazing range of sports clubs and societies, plus the vibrant city of Nottingham on your doorstep, you’ll find plenty of ways to connect and thrive.
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