PhD in Railway Inspection and Maintenance

PGR-P-2518

Key facts

Type of research degree: PhD
Application deadline: Friday 30 April 2027
Project start date: Friday 1 October 2027
Country eligibility: International (open to all nationalities, including the UK)
Funding: Non-funded
Supervisors: Professor David Connolly
Schools: School of Civil Engineering

<h2 class="heading hide-accessible">Summary</h2>

Railway systems continue to present major research challenges as infrastructure ages and transport demands increase. This research theme focuses on developing innovative solutions for railway infrastructure monitoring, specifically targeting remote track inspection and maintenance. Core areas of investigation involve using advanced sensing platforms, including 3D scanning, computer vision, and Augmented Reality, alongside train, UAV, and satellite borne sensing systems. By integrating these emerging digital technologies into traditional railway track engineering, the theme aims to systematically reduce trackside risk for personnel and lower structural inspection costs across the network. Projects within this theme can be tailored to align with your specific digital or track engineering interests. The ultimate goal is to move beyond manual monitoring regimes toward an automated, predictive paradigm that ensures the continuous safety and structural integrity of physical railway tracks and assets.

<h2 class="heading hide-accessible">Full description</h2>

<h3 data-path-to-node="4">Detailed Description</h3> The efficient management of modern railway infrastructure is severely constrained by aging assets and intensifying operational demands. Traditional track inspection techniques rely heavily on manual, visual walkouts or dedicated, expensive geometry trains. These methods provide only periodic snapshots of asset health and disrupt busy timetables. This research theme explores how multi platform remote sensing and digital tools can be used to achieve continuous, non disruptive track tracking. Research within this theme investigates the combination of diverse data streams to monitor track geometry, ballast degradation, component wear, and structural defects in real time. You will look at how high resolution 3D scanning and computer vision can be deployed on operational trains and unmanned aerial vehicles (UAVs) to automate defect classification. The theme also covers the integration of spaceborne radar and satellite observation with train borne sensors to track network scale settlement and track deterioration. Furthermore, we look at how Augmented Reality can be used to present this rich track asset data to maintenance teams, enabling faster and safer precision repairs. By matching digital technologies with structural track mechanics, this theme seeks to build robust frameworks for automated railway maintenance. <h3 data-path-to-node="7">Why This Research is Important</h3> Railway networks serve as critical economic arteries, but maintaining them under rising traffic volumes is increasingly costly and dangerous. Sending human inspectors trackside carries an inherent safety risk and frequently requires expensive line closures that trigger widespread travel delays. Furthermore, as rail infrastructure ages, undetected subgrade erosion, ballast degradation, or rail defects can lead to catastrophic derailments, causing major structural damage and risking lives. This research theme is vital because it addresses the core safety, economic, and operational challenges facing modern rail networks. Automating data collection via spaceborne, airborne, and train borne sensors removes personnel from dangerous trackside environments. It also allows network operators to replace reactive fixes with proactive, targeted maintenance, driving down structural inspection costs significantly. Ultimately, this research ensures that railway track systems remain highly reliable, economically viable, and resilient to long term wear. <h3 data-path-to-node="10">Example PhD Research Topics</h3> <ul data-path-to-node="11"> <li> Automated rail surface defect detection using vehicle mounted computer vision systems </li> <li> Integrating UAV imagery and 3D laser scanning for automated railway track inspection </li> <li> Augmented Reality frameworks for improving accuracy and safety during complex track maintenance tasks </li> <li> Data fusion architectures combining satellite radar data with train borne sensors for track subsidence tracking </li> <li> Predictive maintenance scheduling for ballasted tracks based on automated geometric degradation models </li> <li> Developing machine learning algorithms for real time structural anomaly detection in railway track components </li> </ul> <h3 data-path-to-node="12">Methods and Techniques</h3> <ul data-path-to-node="13"> <li> Computer vision, object detection, and image processing for track component defect mapping </li> <li> Point cloud processing and feature extraction from mobile 3D laser scanning platforms </li> <li> Time series data analytics and machine learning for predictive track failure modeling </li> <li> GIS and spatial data modeling for network scale risk mapping and asset management </li> <li> Core structural health monitoring principles and sensor data integration </li> <li> Digital twin framework design for simulating track deterioration and maintenance interventions </li> </ul> <h3 data-path-to-node="14">Suitable Academic Backgrounds</h3> <ul data-path-to-node="15"> <li> Civil Engineering or Structural Engineering </li> <li> Railway Engineering or Transportation Engineering </li> <li> Computer Science, Data Science, or Artificial Intelligence </li> <li> Geomatics, Remote Sensing, or Robotic Engineering </li> <li> Mechanical Engineering or Applied Physics </li> </ul> <h3 data-path-to-node="16">FAQ</h3> <ul data-path-to-node="17"> <li> Can I propose my own PhD topic? Yes, the themes above are a guide only. </li> <li> Can I bring my own funding? Yes, I welcome applicants who are funded through government scholarships, employers or self funding. </li> <li> Do I need funding before contacting you? You should have at least identified your planned funder and commenced your application. </li> <li> Can I study interdisciplinary topics? Yes. Many of my current research interests combine multiple disciplines. </li> <li> When can I start? Start dates are in spring and autumn. Full details dates are available elsewhere on the University website. </li> </ul> Useful links <ul> <li data-path-to-node="15,0,0" style="margin-left:8px"><a href="https://eps.leeds.ac.uk/civil-engineering/staff/1204/prof-david-p-connolly" style="color:#467886; text-decoration:underline">University Profile</a> </li> <li data-path-to-node="15,1,0" style="margin-left:8px"><a href="https://www.linkedin.com/in/drdavidconnolly/" style="color:#467886; text-decoration:underline">LinkedIn</a></li> <li data-path-to-node="15,2,0" style="margin-left:8px"><a href="https://scholar.google.com/citations?user=jzkpu9IAAAAJ&hl=en" style="color:#467886; text-decoration:underline">Google Scholar</a></li> <li data-path-to-node="15,3,0" style="margin-left:8px"><a href="https://www.researchgate.net/profile/David-Connolly-7" style="color:#467886; text-decoration:underline">ResearchGate</a></li> <li data-path-to-node="15,4,0" style="margin-left:8px"><a href="https://orcid.org/0000-0002-3950-8704" style="color:#467886; text-decoration:underline">ORCID</a></li> <li data-path-to-node="15,5,0" style="margin-left:8px"><a href="https://www.scopus.com/authid/detail.uri?authorId=35098220800" style="color:#467886; text-decoration:underline">Scopus</a></li> </ul>

<h2 class="heading">How to apply</h2>

To apply for this project you will need to make a formal application for research degree study through the <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">University website</a>. You will need to create a login ID with a username and PIN. • For Application type please select Research Degrees – Research Postgraduate. • The admission year for this project is 2027/28 Academic Year. • You will need to select your Planned Course of Study from a drop-down menu. For this project, scroll down and select PHP Civil Engineering Full Time. • The project start date for this project is 1 October 2027, please use this as your Proposed Start Date of Research. • Please state clearly in the Research Information Section that the research degree you wish to be considered for is PhD in Railway Inspection and Maintenance as well as <a href="https://eps.leeds.ac.uk/civil-engineering/staff/1204/prof-david-p-connolly">Professor David Connolly</a> as your proposed supervisor . Please state clearly in the Finance section, the funding that you are applying for, if you are self-funding or externally sponsored. More information on how to apply is available on our website <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">here</a>. You will be required to provide a personal statement which outlines your interest in the project you are applying for, why you have chosen it and how your skills map onto the requirements of the project. We will assess applications continuously as we receive them. We welcome and strongly encourage any potential applicants to contact the supervisor(s) for an informal discussion, prior to applying, and recommend submitting your application early. If you are applying with external sponsorship or you are funding your own study, please ensure you provide your supporting documents at the point you submit your application: <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date including the grading scheme</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> </ul> If English is not your first language, you must provide evidence that you meet the University's minimum English language requirements (below). As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability.

<h2 class="heading heading--sm">Entry requirements</h2>

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.

<h2 class="heading heading--sm">English language requirements</h2>

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.

<h2 class="heading">Funding on offer</h2>

This is a non funded PhD project. Applicants are expected to be self funded or to secure external funding. You can find out more about our Funding Opportunities on our <a href="https://phd.leeds.ac.uk/">Postgraduate Research Opportunities</a> website. Important: Please note that all costs associated with your arrival at Leeds (<a href="https://www.leeds.ac.uk/international-visas-immigration/doc/applying-student-visa">visa, Immigration Health Surcharge</a>, flights etc) would have to be met by yourself, or you will need to find an alternative funding source.

<h2 class="heading">Contact details</h2>

For further information about your application, please contact PGR Admissions by email to <a href="mailto:phd@engineering.leeds.ac.uk">phd@engineering.leeds.ac.uk</a> For further information about this project, please contact Professor David Connolly by email to <a href="mailto:D.Connolly@leeds.ac.uk">D.Connolly@leeds.ac.uk</a>