MPhil/PhD Studentship in Physics-Informed Vibration-Based Structural Health Monitoring of Wheel-Rail Contact Defects.

Investing in excellence: studentship opportunities

The University of Derby has an opportunity for a full-time postgraduate research studentship in the Data Science and Zero Carbon areas of research in the College of Science and Engineering.

The successful applicant will receive a maintenance stipend (based on the minimum stipend defined by UKRI, currently £21,805 for the academic year 2026/27) and home MPhil/PhD tuition fees (£5,238 - subject to amendment) only up to the target submission date.

The intended intake period is January 2027.

International applicants may need to defer to March 2027 to allow sufficient time for CAS issuance and visa processing.

Please note: If your application is successful and you are assessed as international for fees purposes, you will need to pay the difference between the home fees and the international fees.

The successful applicant will be expected to complete their MPhil/PhD within 3 years on the MPhil/PhD route, contribute to the College REF submission and get involved in the wider research activities of the College.

Applicants will become part of a friendly and welcoming team and will be supported and managed by their supervisors.

The vacancy details are as follows:

Project description

This project will investigate how vibration measurements and physics-informed machine learning (PIML) can be used to monitor the health of the wheel-rail contact system in railway vehicles. Wheel and rail defects, including wheel flats, corrugation and localised damage, generate characteristic vibration signatures that can be detected using appropriate sensors. However, conventional machine-learning approaches can require large datasets and may struggle when operating conditions change.

The project will combine railway vehicle dynamics, vibration analysis, experimental testing and artificial intelligence to develop a robust and interpretable monitoring system. The successful candidate will develop physics-based models of wheel-rail interaction, generate and analyse vibration datasets, and develop machine-learning algorithms constrained by fundamental physical principles. The research will involve numerical modelling, signal processing, laboratory experimentation and validation of the proposed approach.

The project provides an opportunity to work at the intersection of mechanical or railway engineering, dynamics and vibration, numerical modelling, signal processing, and machine learning, addressing an important challenge in the development of safer, smarter and more sustainable railway systems.

Purpose and Objectives

The purpose of the project is to develop an intelligent, physics-informed approach for early detection and assessment of wheel-rail defects using vibration measurements.

The successful candidate will:

• Develop a physics-based dynamic model of the wheel-rail contact system
• Investigate vibration signatures associated with different wheel and rail defects
• Develop and train a physics-informed machine-learning framework for defect detection and severity assessment
• Validate and benchmark the approach using experimental data (and potentially representative field dataset)

Potential project impact

The project has the potential to advance railway condition monitoring by enabling more continuous, automated and reliable assessment of wheel-rail health. By combining engineering physics with AI, the research aims to overcome limitations associated with purely data-driven monitoring approaches.

Potential impacts include:

• Safer railways: Earlier identification of developing wheel and rail defects could support proactive intervention and reduce safety risks
• Smarter maintenance: Improved condition monitoring could enable predictive and condition-based maintenance, reducing inspection requirements, downtime and maintenance costs
• Sustainable rail innovation: The research will support a sustainable railway infrastructure, such as extending asset life, reducing unnecessary replacement and inspection, and supporting more resource-efficient maintenance. It will also strengthen collaboration between the University, railway industry and technology partners, contributing to the development of next-generation digital railway systems.

To apply

Please review our entry requirements before submitting your application and check out the 'Getting Started' section below.

Completed applications should be submitted via our online application system. It is important that you quote the funding reference: QR_SE_VIBRATION_2627

Apply online

Closing dates for applications: 8 November 2026.

Interviews: 20 November 2026 to 26 November 2026.

If you have not been invited for an interview by the interview date, please assume your application has been unsuccessful.

For other enquiries which are subject-specific please contact:

Dr Uchenna Diala - U.Diala@derby.ac.uk

Dr Parvaneh Zare - P.Zare@derby.ac.uk

Getting started

Before you begin your application, make sure you have the following:

Studentship funding reference code

It is important that you quote the funding reference: QR_SE_VIBRATION_2627 in your application, at the top of your personal statement.

Required Documents

Before submitting your application, please ensure you upload all required documents to enable us to assess your application fully. References may be provided at a later stage.

Personal statement

A 500-word personal statement outlining your suitability for the studentship project. This is a mandatory requirement and you must upload it into your application. You should include your reasons for applying for the studentship, your experience in the field, how you feel you would benefit from studying and relevant information about your previous studies.

Your CV

A CV outlining your academic and professional experience.

Qualifications

Your qualification details including grades and dates taken. You will have the opportunity to upload scanned copies of your qualification certificates and transcripts in the application. If you have no formal qualifications, you can also state this in your application.

Photo ID

A scanned copy of your photo ID, such as a passport or driving licence. This will help us verify your application to study with us.

Academic references

Two signed academic references. This is optional at application stage but highly encouraged. If successful in your application, two academic references will be a mandatory requirement of admission. The references should be in written format, signed and dated from either a supervisor or tutor from your most recent studies.

For international applicants

The University of Derby has a network of international agents and representatives in different regions. For postgraduate research degree applications, depending on your country of origin, you may need to apply through an agent. You can contact any of our agents and apply to study with us through them.

Some agents may charge for provision of services so please check this directly with the agent. Please be aware that, if you apply directly to the University without going through an agent, we may contact you and you will be required to re-apply through an agent or representative before your application can be considered.