Postdoctoral Research Fellow

University of Exeter - Computer Science

This post is available immediately until 30 April 2021 to work on the NERC funded BigFoot project.

The University of Exeter is a Russell Group university that combines world-class research with very high levels of student satisfaction. Exeter has over 21,000 students from more than 130 different countries and is in the top 1% of universities in the world with 98% of its research rated as being of international quality. Our research focuses on some of the most fundamental issues facing humankind today.

The BigFoot project is concerned with the estimation of windstorm footprints in the UK and aims to develop machine learning algorithms to detect and estimate impacts of windstorms using both conventional and unconventional data. The project will exploit data sources such as amateur observations available through the Met Office weather observations website, comments made on social media and video recorded on social media or CCTV, develop, test, and compare statistical process modelling and machine learning based approaches on the information extracted, and establish improvements in consultation with stakeholders.

Wind storms can cause great damage to property and infrastructure. The windstorm footprint (a map of maximum wind gust speed over 3 days) is an important summary of the hazard of great relevance to the insurance industry and to infrastructure providers. Windstorm footprints are conventionally estimated from meteorological data and numerical weather model analyses. However, there are several interesting less structured data sources that could contribute to the estimation, and more importantly will raise the spatial resolution. This is important as there are important small-scale meteorological phenomena that are currently not well resolved by the current methods.

We are recruiting two posts to develop statistical and machine learning approaches to the problem. This post will work with Prof Jonathan Fieldsend and Prof Richard Everson on the development of machine learning algorithms.

The successful applicant will be able to develop and apply machine learning algorithms. Experience of using machine learning methods for spatially and temporally coupled data will be advantageous.

Applicants will possess a relevant PhD, or equivalent, and be able to demonstrate sufficient knowledge in the discipline to work within established research programmes. They will also need to be able to present information on research progress and outcomes, communicate complex information, orally, in writing and electronically.

The University offers some fantastic benefits including 41 days leave per year, options for flexible working, numerous discounts at leading retailers, an onsite gym, free yoga and pilates, a cycle to work scheme and a stunning campus environment in the heart of Exeter. If you are not currently in Exeter please have a look at our website (www.exeter.ac.uk/thesouthwest) for some further information on what a beautiful part of the country we are based in.

For further information please contact Prof Jonathan Fieldsend J.E.Fieldsend@exeter.ac.uk or (01392 722090) or Prof Richard Everson R.M.Everson@exeter.ac.uk or (01392 724065).

The Computer Science Departments have a Silver Athena SWAN award as a commitment to providing equality of opportunity and advancing the representation of women in STEM/M subjects.

The University of Exeter is an equal opportunity employer. We are officially recognised as a Disability Confident employer and an Athena Swan accredited institution. Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented in the workforce.

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