AI-Integrated Urban Flood Modelling with Adaptive Building Design for Climate-Resilient UK Cities.

Edinburgh Napier University is seeking a candidate for a research position focused on AI-Integrated Urban Flood Modelling and Adaptive Building Design to enhance climate resilience in UK cities. The role involves developing a framework that links urban flood modelling with adaptive building design, addressing the challenges posed by climate change. Candidates should have a degree in Civil Engineering, Environmental Science, or related fields, along with experience in hydrological modelling and machine learning.
Urban flooding is becoming increasingly frequent and severe across the UK due to climate change, ageing infrastructure, and intensified land use. Over 5.2 million properties are currently at risk, with projected annual damages exceeding £1.3 billion by 2080 under high-emission scenarios (Environment Agency, 2021). Traditional flood mitigation measures—such as engineered barriers and drainage upgrades—are proving inadequate in densely built environments. Adaptive building design, which incorporates elevated structures, permeable materials, and passive drainage systems, offers a promising complement to urban flood modelling. However, integration between hydrological modelling and architectural design remains limited, often fragmented across disciplines. Recent advances in artificial intelligence (AI), geospatial analysis, and machine learning enable dynamic flood forecasting and scenario simulation, yet their application to building-level adaptation is underdeveloped (Zhou et al., 2022; Papacharalampous & Tyralis, 2023). This research addresses a critical gap by developing a framework that links urban flood modelling with adaptive building design, using AI to simulate flood scenarios and inform resilient architectural responses. The study aligns with the UK’s National Flood and Coastal Erosion Risk Management Strategy (DEFRA, 2020) and supports the Climate Resilient Places priority outlined in the UK Climate Change Risk Assessment (CCC, 2021).

Aim
• To develop and validate an integrated framework that combines urban flood modelling with adaptive building design using AI, enhancing climate resilience in flood-prone urban areas across the UK.

Research Questions
• How can AI-enhanced urban flood models be used to inform adaptive building design at the neighbourhood and site scale?
• What are the most effective building adaptation strategies for different flood typologies and intensities?
• How does the integrated framework improve resilience outcomes compared to conventional design and planning approaches?

Academic qualifications

A first degree (at least a 2.2) ideally in Civil engineering, Environmental Science/Engineering, Construction or Architectural technology.

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential attributes:
• Good fundamental knowledge of Civil Engineering and Environmental Science
• Experienced in hydrological modelling and should understand machine learning

Desirable attributes:
• Understanding of building design

When applying click here

APPLICATION CHECKLIST
• Completed application form
• CV
• 2 academic references, using the Postgraduate Educational Reference Form (download)
• Research project outline of 2 pages (list of references excluded). The outline may provide details about:
• Background and motivation of the project. The motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
• Research questions or objectives.
• Methodology: types of data to be used, approach to data collection, and data analysis methods.
• List of references.

The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.
• Statement no longer than 1 page describing your motivations and fit with the project.
• Evidence of proficiency in English (if appropriate)

To be considered, the application must use
• the advertised title as project title

For informal enquiries about this PhD project, please contact Dr Nimi Dan-Jumbo - N.Dan-Jumbo@napier.ac.uk