PhD in Model-Based Systems Engineering

The UK’s nuclear decommissioning programme faces a critical knowledge challenge. Decades of operations have produced vast archives of documents, drawings, and records—many only recently digitised. These materials are often fragmented and difficult to interpret without the expertise of staff who are ageing and retiring. This loss of tacit knowledge threatens safety, efficiency, and the ability to train future specialists./nThis EngD project will explore how existing AI technologies, such as large language models, can be adapted for nuclear decommissioning knowledge retrieval while addressing their current limitations: lack of transparency, traceability, and engineering context. The researcher will develop methods to combine AI with Model-Based Systems Engineering (MBSE) principles, creating a structured backbone that links AI-generated insights to plant systems, processes, and original data sources. This approach will make AI outputs more verifiable, auditable, and trustworthy./nThe outcome will be a proof-of-concept platform tested on real decommissioning data, demonstrating how AI and MBSE can work together to preserve knowledge, support safe decommissioning, and accelerate workforce training. This research will help transform decades of legacy information into a reliable digital resource for the UK’s nuclear future. Location: Loughborough