University: University of Nottingham
Faculty: Faculty of Engineering
Research group: Resilience Engineering research group
Location: Nottingham, United Kingdom
Duration: 3.5 years
Supervisor: Dr Rasa Remenyte-Prescott
Start date: October 2026
Funding: UK/home tuition fees plus a tax-free stipend of £22,000 per annum for 3.5 years, with travel and consumables allowance.
Deadline: Aug 8, 2026
Project focus:
This PhD develops a comprehensive railway network delay propagation model to represent disruptions, delay propagation, and operational response strategies. The project is designed to support operational decision-making and improve railway network performance under disturbance.
Research themes:
The study uses analytical and AI methodologies together with multi-objective optimisation. The aim is to balance resilience, efficiency, and network performance, while producing interventions that are timely and effective. The project also has a strong applied component through collaboration with Network Rail and access to real-world railway operations data.
Candidate profile:
The advert asks for an enthusiastic graduate with a first-class degree in engineering, mathematics, or a relevant discipline, preferably at master’s level; in exceptional circumstances, a 2:1 may be considered. The studentship is restricted to UK/home candidates only.
Application process:
Applications are made online through the advert’s Apply button, and the position is open until filled. The advert recommends early application and gives Dr Rasa Remenyte-Prescott’s email for queries about the project or funding.
Impact and collaboration:
The project is explicitly framed as a chance to influence the future resilience of UK railway operations through advanced modelling and AI. It is also intended to give the student practical exposure to digital railway challenges and operational datasets.
https://www.jobs.ac.uk/job/DRL875/phd-studentship-ai-based-approaches-for-improved-railway-network-resilience
