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University of Leeds, Faculty of Environment Civil & Structural Engineering PhD Projects, Programs & Scholarships

We have 5 University of Leeds, Faculty of Environment Civil & Structural Engineering PhD Projects, Programs & Scholarships

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  Adapting Road Infrastructure for Autonomous Vehicles
  Dr Y Huang, Prof O Carsten, Dr J Wang
Application Deadline: 31 January 2020

Funding Type

PhD Type

Autonomous vehicles are emerging as a solution to human driver limitations, such as imprecise control of speed and road position.
  Combining machine learning and decision science to model transport and energy choices using emerging data sources
  Dr C Choudhury, Prof S Hess
Application Deadline: 31 January 2020

Funding Type

PhD Type

Machine learning and choice modelling techniques have been developed in parallel as tools for modelling human decisions.
  Landslide nowcasting using advanced data analytics
  Dr A Abellan, Dr B Murphy, Prof T Wright
Application Deadline: 31 January 2020

Funding Type

PhD Type

The fast proliferation of new satellite, aerial and terrestrial remote sensing techniques has provided new technological and scientific opportunities to investigate geohazards during the last decade.
  On solid ground? Predicting high-speed railway track settlement using geophysical analysis.
  Dr S de Ridder, Dr A Booth, Dr P Livermore
Application Deadline: 31 January 2020

Funding Type

PhD Type

High-speed trains induce a small level of permanent settlement within their supporting railway track and ground during passage. The settlement grows over time, but the degree of settlement varies along the track depending upon geographical changes in ground conditions.
  Using distributed immersive simulation to explore social interactions between drivers
  Prof R Romano, Prof D P Watling
Application Deadline: 31 January 2020

Funding Type

PhD Type

Transport system designers need to understand and predict the impact of new infrastructure design. This can include automated vehicles in ‘mixed traffic’ situations, in which both automated and non-automated vehicles are on the road.
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