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Dr N Malleson
No more applications being accepted
Funded PhD Project (European/UK Students Only)
About the Project
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 at the Leeds Institute for Data Analytics who are working together to improve the ways that scientists can model cities.
More specifically, the successful candidate for this project will 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 such a model in 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. Models such as the one produced by this PhD project could be extremely valuable because they will help scientists and policy makers to better understand the daily pulse of a city, and to then find ways to make cities better by (for example) reducing pollution in the places where most people are exposed, or better understanding where crime rates are significantly higher than elsewhere.
How to apply http://www.geog.leeds.ac.uk/study/phd/how-to-apply/
More specifically, the successful candidate for this project will 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 such a model in 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. Models such as the one produced by this PhD project could be extremely valuable because they will help scientists and policy makers to better understand the daily pulse of a city, and to then find ways to make cities better by (for example) reducing pollution in the places where most people are exposed, or better understanding where crime rates are significantly higher than elsewhere.
How to apply http://www.geog.leeds.ac.uk/study/phd/how-to-apply/
Funding Notes
Start date: 1 October 2018
The studentship covers UK/EU tuition fees and a tax-free maintenance stipend of ~£14,777* pa for 4 years.
*The maintenance level will be reviewed annually in line with the UK Research Council rates https://www.ukri.org/skills/funding-for-research-training/
Eligibility
Applications are welcome from UK/EU applicants who have, or expect to receive by July 2018, 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.
The studentship covers UK/EU tuition fees and a tax-free maintenance stipend of ~£14,777* pa for 4 years.
*The maintenance level will be reviewed annually in line with the UK Research Council rates https://www.ukri.org/skills/funding-for-research-training/
Eligibility
Applications are welcome from UK/EU applicants who have, or expect to receive by July 2018, 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.