Sequence Modelling Using Deep Learning Approaches for Streaming Spatio-temporal Public Transport Data

This project focuses on the application of advanced deep learning algorithms to robust predictive modelling of spatio-temporal data streams in the context of city-wide transport network and propagation of disruptions therein. One of the key challenges in the UK’s increasingly congested conurbations is modelling the movement of vehicles in order to identify bottlenecks and delays before they occur, and to provide the road and public transport users with relevant and timely information.

How to apply:
Applications are made via our website using the Apply Online button below. If you have an enquiry about this project please contact us via the Email NOW button below, however your application will only be processed once you have submitted an application form as opposed to emailing your CV to us.
Candidates for funded PhD studentship must demonstrate outstanding qualities and be motivated to complete a PhD in 4 years.
The PhD Studentships are open to UK, EU and international students. Candidates for a PhD Studentship should demonstrate outstanding qualities and be motivated to complete a PhD in 4 years and must demonstrate:

• A 1st class honours degree and/or a relevant Master’s degree with distinction or equivalent.If English is not your first language you’ll need IELTS (Academic) score of 6.5 minimum (with a minimum 6.0 in each component).