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School of Geography

Data Assimilation for Agent-Based Models (DUST) PhD studentships

The following PhD projects are fully funded covering UK/EU fees and a tax-free stipend for 4 years.  The maintenance allowance for 2018/19 will be £14,777 and this will be reviewed annually in line with the UK Research Council rates

Start date: 1 October 2018
Closing date for applications: Extended to 30 April 2018

1. Developing Model Ensembles and Emulators for Next-Generation City Simulation

Principal supervisor: Dr Nick Malleson

This PhD project will be part of an exciting new initiative entitled “Data Assimilation for Agent-Based Models (DUST)” (https://dust.leeds.ac.uk/). The project will develop important new methods that can be used to integrate data that emerge from smart cities (e.g. traffic counters, social media activity, environment sensors, etc.) into large-scale urban simulations in real time. This is an important methodological challenge that has yet to be overcome. Without these, it is very difficult to understand how to manage cities in the short-term, or how to respond in situations that require dramatic interventions such as an evacuation. The successful applicant will join a team of PhD students and researchers who are working together to improve the ways that scientists can model cities.

This PhD will contribute to the project by developing companion methods that allow simulations, such as agent-based models, to be rigorously applied to the real-world. Ensembles are groups of models that are executed in parallel to provide a means of exploring the range of possible outcomes from probabilistic models. These are an ideal way to better understand uncertainty in model results, but are not regularly used in the field of agent-based modelling. A related concept, emulators, refers to simple models that approximate a more complex and computationally demanding model. Developing good emulators for agent-based models could be extremely valuable, especially in the context of running ensembles of hundreds or thousands of models, but again have not been extensively used in the field. This PhD will extend the state-of-the art in methods such as emulators and ensembles – and other techniques such as Bayesian inference that might be appropriate – to allow the urban simulations that are developed as part of DUST to be applied to real-world urban systems.


2. Agent-Based Modelling of Smart Cities

Principal supervisor: Dr Nick Malleson

This PhD project will be part of an exciting new initiative entitled “Data Assimilation for Agent-Based Models (DUST)” (https://dust.leeds.ac.uk/). The project will develop important new methods that can be used to integrate data that emerge from smart cities (e.g. traffic counters, social media activity, environment sensors, etc.) into large-scale urban simulations in real time. This is an important methodological challenge that has yet to be overcome. Without these, it is very difficult to understand how to manage cities in the short-term, or how to respond in situations that require dramatic interventions such as an evacuation. The successful applicant will join a team of PhD students and researchers who are working together to improve the ways that scientists can model cities.

This PhD will contribute to the DUST project by working with others on the project team to develop a large-scale model of urban flows – i.e. a model of the movement of people as they travel around a city. In particular, the project will explore the potential uses of agent-based urban models in application areas such as urban management (can models help us to better understand how spaces are being used?) and evacuation planning (by better understanding urban flows in normal circumstances, can we develop better plans for emergencies that require city-centre evacuation?). An important aspect of the work will be the consideration of how ‘big data’, that are generated in abundance in smart cities, can be used to improve the realism of simulations. Here, methods from data science and urban analytics will be invaluable.

Eligibility
Applications are welcomed from UK or EU citizens with at least a UK 2i/1st class BA/BSc honours degree (or equivalent) in a relevant discipline.  A Masters degree would be advantageous but is not required. 

How to apply
Please submit a PhD application to the School of Geography as outlined on our "How to apply" page by 30 April 2018