Location: UK Other
Closing Date: Sunday 31 December 2023
Reference: ENG1673

Supervised by: Rasa Remenyte-Prescott (Resilience Engineering, Faculty of Engineering) 

Aim: To investigate and develop an approach for evaluating railway resilience through considering railway faults and disruptions


Currently railway safety evaluation is carried out using traditional techniques for identifying potential hazards and determining their frequency of occurrence and the resulting consequences. In addition to component and system failures and human errors, nowadays complex systems such as railways are subject to a range of additional threats, such as terrorism, cyber-attacks and wider technology-based vulnerabilities, as well as being significantly affected by natural hazards and climate change. This is a major challenge, especially when increasingly clear implications of climate change, such as severe weather, can cause a loss of life, such as in the Carmont derailment in 2020. Recent advances in resilience engineering offer a strong alternative to traditional approaches in evaluating railway safety, especially when railway services are expected to be safe, reliable and resilient (i.e. able “to anticipate, absorb, adapt to and/or rapidly recover from a disruptive event”, as per resilience definition by the UK Government).

Proposed project

The proposed project will be based on simulation and analysis of disruption scenarios on the network, which will be used to analyse the effects of these disruptions, depending on their location, passenger numbers affected, frequency and severity of consequences. Vulnerable parts of the network will be identified and analysed in terms of different threat types. This type of analysis can be used to evaluate current operation and maintenance standards and their effectiveness for reducing overall railways system risk and improving resilience to threats. In addition, an optimisation framework can be developed in order to propose best response strategies when threats occur. 

Such a methodology can then be used to make better-informed decisions in railway operation and maintenance. It can potentially improve railway network resilience by reducing vulnerability to threats, such as deteriorated infrastructure, natural hazards and cyber-attacks, and enhance network recoverability by enabling prompt responses and minimising consequences

Summary: Open to UK/EU/overseas students. Look for funding sources at

Entry Requirements: Starting October 2023, we require an enthusiastic graduate with a 1st class degree in engineering, computer science, maths, or a relevant discipline, at integrated Master’s level or with a relevant MSc (in exceptional circumstances a 2:1 degree can be considered). 

To apply visit: 

For any enquiries about the project and the funding please email Rasa Remenyte-Prescott (

Early application is strongly encouraged.

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