Program Overview

Overview

This project will use emergent satellite monitoring techniques to prevent coastal infrastructure and embankment failures. This is part of the Net Zero Maritime Energy Solutions (N0MES) Centre for Doctoral Training, creating the specialist future workforce needed to support renewable energy generation – including coastal infrastructure maintenance. These PhD projects, in collaboration with industrial partners, are finding solutions to urgent industrial needs.

About this Opportunity

This project is funded by the Net Zero Maritime Energy Solutions Centre for Doctoral Training (N0MES CDT) in the University of Liverpool. N0MES offers 4-year PhD studentships for exceptional researchers. With the support of the University of Liverpool (UoL), Liverpool John Moores University (LJMU) and over 30 maritime energy sector partners, N0MES postgraduate researchers will pursue new, engineering-centred, interdisciplinary research in a highly collaborative environment.

Project Outline

Coastal infrastructure, embankments and port assets, are essential for economic growth and exploitation of offshore renewable energy. As these assets age and suffer adverse impacts from the climate emergency, they are more becoming more likely to fail whilst being increasingly essential for coastal operations. Whilst sensor-based monitoring systems allow engineers to monitor the performance of infrastructure assets, these are expensive to install, operate and maintain, which limits them to specific locations. Remote satellite monitoring offers a new method for detecting potential failures and enhancing the resilience of civil infrastructure.

This project will explore using remote satellite monitoring data to predict embankment failures. It proposes to use InSAR data from open-access Sentinel-1 ESA data (used for monitoring ground movements), optical multi-spectral data from Sentinel-2 (that can remotely monitor groundwater levels), and knowledge about ground conditions and hydrogeological information to create a new risk model to inform asset owners of the areas at the highest risk of failure. This will be achieved at a network scale using novel machine learning methods, trained on a series of known previous failures, with the intention of scaling the final methods up for application at a national scale.

Training and Supervision

The successful application will be jointly supervised by Dr Paul Shepley (lead), Dr Eda Majtan and Professor Nicoletta Leonardi who bring geotechnical, fluid-soil-structure interaction, satellite monitoring and machine learning expertise into the project. The project work will be supported by stakeholders and other industrial partners with experience with satellite monitoring, data science and critical infrastructure assessments that will benefit from the methods under development during the research. The student will also have access to the Geographic Data Science Lab at the University of Liverpool.

Project Structure

A candidate with experience in one part of the project (e.g. geotechnical/geological, fluid-soil interaction or satellite monitoring/machine learning) will be provided with training and support during their first year of studies, through the N0MES CDT. You will be a member of the N0MES CDT cohort and encouraged to attend affiliated events and seminars – an additional opportunity to join like-minded students working on offshore marine energy projects and become part of a thriving research community. Subsequent years will focus on independent research working across disciplines to produce an efficient, scalable tool for predicting infrastructure failures using remote sensing methods.

Who is this For?

Candidates will have, or be due to obtain, a Master's Degree or equivalent in a relevant subject. Exceptional candidates with a First Class Bachelor's Degree in an appropriate field or significant relevant experience will also be considered.

How to Apply

To apply for this PhD project, candidates should:

• Complete the University of Liverpool application form to apply for a PhD in Civil Engineering.
• Ensure to include the project title and reference number NOMES004 when applying.
• Prepare the necessary application documents, which may include:
  • A research proposal
  • University transcripts and degree certificates to date
  • Passport details (for international applicants only)
  • English language certificates (for international applicants only)
  • A personal statement
  • A curriculum vitae (CV)
  • Contact details for two proposed supervisors
  • Names and contact details of two referees.

Funding your PhD

This UKRI funded (via the EPSRC-funded N0MES CDT) Studentship will cover full tuition fees and pay a maintenance grant for 4 years, at the UKRI standard rates. The Studentship also comes with access to additional funding in the form of a Research Training Support Grant to fund consumables, conference attendance, etc. UKRI Studentships are available to any prospective student wishing to apply, including both home and international students. While UKRI funding will not cover international fees, a limited number of scholarships to meet the fee difference will be available to support outstanding international students.