PhD Opportunity in Structural Health Monitoring (‘SHM’) of Civil Infrastructure

University of Surrey - Civil and Environmental Engineering

The University of Surrey are seeking a motivated and enthusiastic Doctoral student to work in a fast-paced, progress-oriented environment.

The safety and integrity of civil infrastructure is a critical concern in our society and a challenge for our research community. To address such issues, next-generation materials and structures have been envisioned as being engineered with smart features and abilities to monitor their own condition through a comprehensive sensor network in either passive or active ways.

These sensors should be able to evaluate structural integrity indicators and provide maintenance/management recommendations. In this respect, the huge quantities of Structural Health Monitoring (SHM) data that can be acquired offer not only opportunities to help engineers improve the safety and maintainability of critical structures, but also introduce new challenges which require further advances in fundamental research and applied technologies.

At Surrey, we have so far investigated a range of issues related to the application of SHM techniques in metallic bridges, pipelines and other structures, bringing together expertise in materials and structures, as well as statistics, informatics and decision theory. Our collaborations with various industry partners enables us to analyse the real data from the critical infrastructure assets.

Entry Requirements

Well qualified and strongly motivated PhD candidates are invited to join an expanding research group working on SHM-based life-cycle asset management.  Applicants will be selected using the following criteria:

  • Applicants should have (or expect to obtain by the start date) at least an Upper Second Bachelor’s degree, and preferably a Master’s degree, in an Engineering subject.
  • Applicants are expected to have excellent analytical skills and a solid background in structural mechanics/dynamics and advanced numerical modelling of structures (e.g., finite element modelling).
  • Applicants with a deep understanding of statistical inference and/or machine learning techniques will be preferred.
  • Relevant professional experience is welcomed.


Funding is available for UK or EU nationals only and covers full tuition fees (home rate) and a stipend at the rate specified by the Research Council (rate for 2017/18 is £14,553 p.a. tax-free). The award will be for a period of 3 years.

How to apply

For further information about this project, please e-mail Tina Looi (

Formal applications can be made through our programme page

The deadline for applications is 31January 2018.

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South East England