Qualification Type: | PhD |
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Location: | Loughborough University, Loughborough |
Funding for: | UK Students, EU Students, International Students |
Funding amount: | £17,668 tax-free stipend |
Hours: | Full Time |
Placed On: | 7th February 2023 |
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Closes: | 17th March 2023 |
Reference: | ABCE-AM-CDT |
Built on the initial work of ‘Applying AI to building blueprints for insurance risk assessment (AURIE)’, this project aims to develop an ontology digital twinning approach to construct the domain knowledge graphs for improved risk assessment and underwriting capability. It will:
Develop an ontological knowledge framework from CAD drawings/BIM models (building ontology), safety codes (safety/risk ontology), and sensor data (occupant behaviour ontology) for risk knowledge modelling of buildings.
Develop a multi-source knowledge fusion method based on the ontology frameworks for a uniform domain knowledge model.
Develop arrangements for automatically querying the uniform knowledge model for risk assessment of buildings.
Explore the practicalities, including software or tool development, for implementing these techniques using the blueprint and other information for commercial and industrial properties available to WTW and WTW clients.
Its ultimate ambition is to transform property insurance risk analysis and underwriting from present arrangements employing extensive manual processing into an automatic and reliable process using ontology digital twins.
This PhD project will be one of six 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 partly 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. For a full description of the mini-CDT, of the individual PhD projects and of the support provided by the WTW Research Network to the mini-CDT see [Mini-Centre of Doctoral Training in Industrial and Commercial Property Insurance – TECHNGI].
Funding
Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Fees are reviewed annually and are likely to increase to take into account inflationary pressures.
The studentship is for 3 years and provides a tax-free stipend of £17,668 a year (2022/23 rate - stipend may rise in line with Research Council recommendations) for the duration of the studentship plus tuition fees at either the UK or International rate.
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