PhD Studentship: Seeing Extreme Winds: Using Video Clips to Quantify Hazardous Winds

Project details

This PhD project will harness the power of developments in image analysis to solve the real-world challenge of estimating wind hazard. This is an exciting opportunity to apply state-of-the-art techniques (e.g. machine learning) to video clips of moving trees, and conduct corresponding fieldwork to develop new understanding of the natural environment and atmospheric processes at work. At the core of the work will be a campus-scale study, with a variety of CCTV camera data linked to data from the university’s weather station. Initially, the project will use data already collected in a pilot study and existing particle-tracking code to create a local (micro-scale) map of wind hazard. There is clear space for a student to excel by creating a step-change in the image analysis techniques. The opportunity also exists for wind tunnel experiments and physical modelling. The final aim is to create a proof-of-concept tool for high-resolution, low-cost mapping (i.e. high/low hazard areas) without installing specific technology such as wind meters, enabling site-specific recommendations on mitigation (e.g. tree planting as a shield).

This PhD project will be one of seven PhD projects being pursued in a cross-disciplinary mini-College of Doctoral Training (mini-CDT) running at Loughborough University from 2022 to 2026. This mini-CDT is part-financed and supported by the WTW Research Network, the award winning collaboration between academia, finance and research industries on the understanding and quantification of risk.

This industry collaboration builds on the earlier partnership between Loughborough University and WTW in the recently completed TECHNGI research project on technology and next generation insurance services. A full description of the mini-CDT, of the individual PhD projects and of the support provided by the WTW Research Network is here.

Supervisors

Primary supervisor/CDT lead: Dr John Hillier

Secondary supervisors: Dr Sarah Bugby and Dr Tim Marjoribanks

Entry requirements

Applicants should have or expect to achieve at least a 2:1 Honours degree (or equivalent). A relevant master’s degree or work experience would be advantageous.

We encourage any applicants with a keen curiosity about the natural environment and technical competence in data handling (e.g. data analysis, image processing, big data). Backgrounds in a variety of fields are suitable e.g. Environmental science, Physics, Geography, Engineering, Computer Science, Data Science.

How to apply

All applications should be made online. Under programme name, select Geography and Environment.

Please quote the advertised reference number: GE23-JH-CDT in your application.

Please upload with your application the following supporting documents:

• A curriculum vitae
• An 800 word covering letter explaining your interest in, and aptitude for, the topic of this research project, and the qualities you can bring to the project
• Copies of your transcripts/certificates, English Language certificate
• The details for two academic referees who will be contacted if you are invited to interview (ideally one from your Masters degree)

To avoid delays in processing your application, please ensure that you submit the minimum supporting documents.

Interviews are due to take place June.

Funding

The studentship is for 3 years and provides a tax-free stipend of £17,668 per annum for the duration of the studentship plus tuition fees at either the UK or International rate.

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