PhD Studentship: AI-based Approaches for Improved Railway Network Resilience

Supervisor: Dr Rasa Remenyte-Prescott - Resilience Engineering research group in the Faculty of Engineering.

Highlights

• Unique opportunity to collaborate with Network Rail and influence the future resilience of railway operations using advanced modelling and AI techniques
• As the UK rail network grows ever more congested, the ability to anticipate, manage, and recover from disruption becomes increasingly vital

Aim

Develop a comprehensive railway network delay propagation model capable of addressing a wide range of disruptions and response strategies.

Background

The railway network in the United Kingdom is both complex and extensive. For example, in 2024 it recorded approximately 1.7 billion passenger journeys, equating to around 4.8 million train movements per day—a 9% increase on the previous year. This growth highlights the critical role of rail in national mobility and the mounting pressure on infrastructure and operations. Despite carefully designed and monitored timetables disruptions occur unexpectedly, often triggered by infrastructure failures, human error, or external factors. Given the high level of network congestion a single incident can propagate delays widely across the system. Timely and effective intervention is therefore essential in mitigating reactionary delay and maintain network resilience.

Proposed project

This 3.5-year PhD project will develop a comprehensive railway network delay propagation model to represent disruptions, delay propagation, and operational response strategies. The ultimate output will be a robust framework to support operational decision making and maintain required network performance. You will investigate the use of analytical and AI methodologies that support a multi-objective optimisation approach, balancing resilience, efficiency, and network performance.

Benefits of joining this project

The project will allow you to collaborate with Network Rail gaining practical experience of the UK’s digital railway challenges through exposure to datasets gathered from real-world railway operations, and developing impactful research outcomes that maximise railway network efficiency through targeted, timely and effective interventions.

Candidate requirements 

Starting October 2026, we require an enthusiastic graduate with a 1st class degree in engineering, maths, or a relevant discipline, preferably at master’s level - in exceptional circumstances a 2:1 degree can be considered.

Funding and eligibility

This studentship is available to UK/home candidates only.

The proposed funding will cover UK / home PhD tuition fees plus a tax-free stipend for 3.5 years starting at £22,000 pa. A travel and consumables allowance will also be available. 

How to apply

Please apply online via the 'Apply' button above. This studentship is open until filled. Early application is strongly encouraged.

For any enquiries about the project or funding please email Dr Rasa Remenyte-Prescott at r.remenyte-prescott@nottingham.ac.uk 

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