Job title:
Civil Engineering: Fully Funded Leverhulme Trust UK PhD Scholarship: Artificial Intelligence-assisted saltmarsh flood mitigation assessment
Company
Job description
Offer Description
Funding providers: Leverhulme Trust UK
Subject areas: Coastal Engineering, Artificial Intelligence
Project start date:
- 1 July 2024 (Enrolment open from mid-June)
Project supervisors:
- Professor Harshinie Karunarathna (
) * Dr Alma Rahat
- Dr John Griffin
Aligned programme of study: PhD in Civil Engineering
Mode of study: Full-time
Project description:
The current estimated damage due to coastal flooding in the UK alone is £540 million/year. Coastal flooding will rapidly increase in future, as the UK is expected to face at least 1m of sea level rise by 2100. The UK Committee on Climate Change acknowledges the urgent need for implementing flood mitigation measures, while the UK Government’s Resilient Nation prosperity outcome recognises the need to implement climate-adaptive flood defences. Coastal wetlands have been recognised as potential buffers against storm impacts, serving as a Nature-based Solution (NbS) for flood mitigation, which have become favoured options over building hard defences. Managed realignment of saltmarshes has already been implemented as flood and coastal erosion control measures in the UK. However, recent research suggests that managing saltmarshes as a flood defence is hindered by unresolved context-dependency where the estuarine environment, marsh morphology and flood drivers) define different contexts. The high computational costs of running computational coastal simulators multiple times over with a diverse and distinct set of parameters and highly specialised multiple skill requirements prohibits a thorough exploration of the parameters that control the efficacy of saltmarshes. As a result, beyond a general recognition that NbS for flood mitigation are inherently context-dependent, it has been difficult to advance i) fundamental understanding of the key drivers of nature-based flood mitigation, and ii) derive explicit recommendations on how best to manage and configure saltmarshes to meet policy demands.
In recent years Artificial Intelligence (AI) has been successfully utilised to solve complex coastal engineering problems. We aim to develop a new data-driven emulation tool to unravel context-dependency and predict flood mitigation of saltmarshes by integrating computational modelling and AI. The primary aim of this PhD project is to establish a new computational model of wave attenuation on coastal vegetation which can be used as a simulator to assist the development of the AI emulator. The project is a part of a larger research grant funded by the Leverhulme Trust, UK. The PhD student will work alongside a postdoctoral researcher and contribute to the development of the AI emulator.
Facilities: The student will become a part of a very dynamic coastal engineering research community who combines coastal engineering with numerous other disciplines to understand coastal change and develop methologies to investigate and forecast coastal change and flood risk. They will have access to a world leading High Performance Computing cluster and a state-of-the-art coastal engineering laboratory experimental facility. This PhD project is funded by the Leverhulme Trust, UK.
Requirements
Research Field Engineering Education Level Master Degree or equivalent
Skills/Qualifications
Candidates must hold an MEng/BEng in Civil/Coastal Engineering with 1st or 2.1 or MSc in Marine Science, Coastal Engineering, Computational Engineering, Ocean engineering or Oceanography. If you are eligible to apply for the scholarship (i.e. a student who is eligible to pay the UK rate of tuition fees) but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency.
Specific Requirements
Desirable skills and attributes:
- Basic knowledge on coastal hydro- and morphodynamics;
- Numerical modelling;
- Statistical methods;
- Willingness to learn computational coastal modelling and Artificial Intelligence.
Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by .
Additional Information
Benefits
This scholarship covers the full cost of UK tuition fees and an annual stipend of £18,622.
Additional research expenses will also be available.
Eligibility criteria
Candidates must hold an MEng/BEng in Civil/Coastal Engineering with 1st or 2.1 or MSc in Marine Science, Coastal Engineering, Computational Engineering, Ocean engineering or Oceanography. If you are eligible to apply for the scholarship (i.e. a student who is eligible to pay the UK rate of tuition fees) but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency.
Desirable skills and attributes:
- Basic knowledge on coastal hydro- and morphodynamics;
- Numerical modelling;
- Statistical methods;
- Willingness to learn computational coastal modelling and Artificial Intelligence.
Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by .
Selection process
Please visit our website for more information.
Website for additional job details
Work Location(s)
Number of offers available 1 Company/Institute Swansea University Country United Kingdom Geofield
Where to apply Website
Contact State/Province
Swansea City
Swansea Website
Street
Singleton Park Postal Code
SA2 8PP
STATUS: EXPIRED
Expected salary
£18622 per year
Location
United Kingdom
Job date
Fri, 19 Jan 2024 00:23:15 GMT
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