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Construction Information Technology Laboratory

 

 The project is a fully funded 4-year EPSRC Industrial CASE PhD Studentship, commencing on 1st October 2021, to investigate methods for generating Digital Twins of roads.

The aim of EPSRC Industrial CASE awards is to provide PhD students with a first-class training experience both in academic and non-academic partner organizations. This project is co-sponsored by Ordnance Survey (OS), a world-leading organisation specializing in surveying the built environment. The work will make use of OS’ extensive visual and spatial datasets of the UK road network collected with unmanned aerial vehicles and state-of-the-art deep learning methods to provide semantic meaning to the raw data and generate Digital Twins of the road network.

The project seeks to better understand the challenges with large scale digital transformation of the built environment. One challenge is in managing big data; the complexity and sheer size of datasets that cover thousands of square miles. Another challenge is understanding what the desired semantic meaning is in the context of road infrastructure and describing it in machine friendly language suitable for training deep learning algorithms. The project will employ a variety of algorithms to manage the data size and complexity and extract semantically meaningful entities suitable for generating reliable Digital Twins.

The project will be jointly supervised by Dr Ioannis Brilakis in the Construction IT group of the Civil Engineering Division at the Department of Engineering, and Dr Stefano Cavazzi from OS.

Applicants should have (or expect to obtain by the start date) at least a good 2.1 degree in an Engineering or related subject.

Deadline was on 30th May 2021.

If you have any questions about this vacancy please contact: Dr I. Brilakis (ib340@cam.ac.uk) for queries of a technical nature related to the role or the CIT Administrator (cit-admin@construction.cam.ac.uk) for the application process.

 

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