PhD Studentship in Advanced Numerical Modelling and Predictive Maintenance of Buried Infrastructure

University of Birmingham; Birmingham; On-site; GBP 20,000 - 24,000; Full time

Job summary

The University of Birmingham invites applications for a PhD project focused on assessing and predicting the performance of buried infrastructure, especially water pipelines and ground instability. The project seeks to combine physics-based modelling with data-driven approaches to identify deterioration and forecast progression, enabling timely maintenance decisions.

You will work within the School of Engineering and NBIF, access a multidisciplinary team, and use experimental datasets including

Qualifications

• A degree in civil/geotechnical/mechanical engineering, applied mathematics, computer science, or related field.
• Strong analytical and mathematical skills with an interest in computational mechanics.
• Experience in programming using Python and C++.
• Good written and verbal communication skills.

Skills

Python

C++

Analytical skills

Communication

Education

First/Upper Second-class honours

Master's degree advantageous

Job description

Buried infrastructure underpins essential urban services, yet its deterioration often remains hidden until significant damage or service disruption occurs. Ageing pipelines face increasing pressures from climate change, groundwater fluctuations and nearby construction. Their integrity is closely linked to the surrounding ground. Pipe defects can initiate water leakage and internal soil erosion, leading to loss of support, subsidence and potentially sinkhole formation. Conversely, ground movement can impose additional stresses on pipelines, accelerating damage and leakage. Understanding and predicting this dynamic, coupled deterioration process is essential for timely and effective maintenance.

This PhD project will develop a hybrid physics-based and data-driven framework for assessing the condition and predicting the performance of buried infrastructure, with a focus on water pipelines and associated ground instability. The central research question is how advanced computational models and monitoring data can be combined to identify infrastructure deterioration and predict its progression towards failure.

The project will innovate computational modelling techniques to simulate interactions between structure damage, water leakage, soil erosion and ground deformation. Building on these physical models, the research will investigate AI-assisted surrogate modelling and data assimilation to connect numerical predictions with monitoring observations, potentially including distributed fibre-optic strain measurements, hydraulic data and ground displacement. The anticipated outcome is a validated computational framework linking deterioration mechanisms, monitoring-informed prediction and maintenance decision-making. The project will support earlier intervention, reduced water losses and service disruption, and greater resilience of buried infrastructure to urban ground hazards.

The successful candidate will be based in the School of Engineering at the University of Birmingham, which hosts the National Buried Infrastructure Facility (NBIF, www.birmingham.ac.uk/nbif). They will have access to advice and support from a multidisciplinary team of experts in numerical modelling, AI-solutions, physical sensing for buried infrastructure, alongside documented experimental datasets obtained using a wide range of instrumentation and measurement techniques, including fibre-optic sensing, laser scanning, and force and strain measurements.

This project is expected to start before/in September 2027.

Requirements

• A First- or Upper Second-class Honours degree, or an equivalent qualification, in civil engineering, geotechnical engineering, mechanical engineering, applied mathematics, computer science or a closely related discipline. A relevant master’s degree and/or research or industry experience would be an advantage.
• Strong analytical and mathematical skills, with an interest in computational mechanics and numerical modelling.
• Experience in programming or scientific computing using languages such as Python, and C++.
• Good written and verbal communication skills.

Funding notes

Funding for this project covers tuition fees (UK/home-student rate), UKRI minimum annual stipend (currently £21,805/annum) for the full duration of the 3.5-year programme. International students are welcome to apply if you are willing to cover the tuition difference between home and international rates through self-funding or external sources. Support will be provided for applications for external funding, such as Commonwealth fellowships or funding from the Schlumberger Foundation and the China Scholarship Council.

£21,805 per annum