PhD project in AI-enhanced study of the origins of railway noise under complex track geometrical conditions
PhD @University of Southampton posted 2 weeks agoJob Description
About the project
This project focuses on railway noise and vibration. By integrating computational modelling, experimental measurements, and AI-driven insights, the research aims to develop predictive models for noise reduction and sustainable railway development.
Railways, including high-speed, conventional, and urban transit systems, are extensively utilized worldwide as efficient, environmentally friendly, and sustainable modes of transport. However, noise and vibration remain critical challenges, impacting passenger comfort, communities near railway lines, and maintenance efforts and costs.
Railway systems operate in varied environments, including severe conditions such as sharply curved sections or switches and crossings, which can lead to high levels of noise. This project aims to develop predictive and AI-enhanced models to study rail and wheel roughness and its impact on noise and vibration under various conditions.
You will establish improved predictive models for railway rolling and impact noise under different operational conditions. You will employ machine learning models to solve the inverse problem of identifying and monitoring roughness growth. You will carried out experimental measurements in the laboratory and field to validate numerical findings and provide data for AI-enhanced models. These efforts will lead to practical noise mitigation and acoustic optimization strategies to improve railway system performance.
This project will contribute to sustainable railway development by addressing the complexities of wheel/rail interactions and their relationship with surface roughness and track geometry in varied operational environments. By integrating advanced computational modelling, field measurements, and AI-driven analytics, this research will offer new insights into noise and vibration reduction, ultimately enhancing passenger comfort and reducing maintenance costs.
Entry requirements
You must have a UK 2:1 honours degree or its international equivalent, in one of the following:
- mechanical engineering
- civil engineering
- transportation engineering
- railway engineering
- acoustics
or a related field.
Preference will be given to candidates with a strong background in numerical modelling, experimental methods, and AI techniques.
Fees and funding
For both UK and international students, tuition fees will be paid and you will receive a stipend (living allowance).
How to apply
You need to:
- choose programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences
- select Full time or Part time
- choose the relevant PhD in Engineering
- add name of the supervisor in section 2
Applications should include:
- a personal statement
- your CV (resumé)
- 2 academic references
- degree transcripts to date
Contact us
Faculty of Engineering and Physical Sciences
If you have a general question, email our doctoral college (feps-pgr-apply@soton.ac.uk).
Project leader
For an initial conversation, email Dr Wenjing Sun (W.Sun@soton.ac.uk).
