Agent-Based Modelling of Smart Cities
This PhD project is part of an exciting new initiative entitled “Data Assimilation for Agent-Based Models (DUST)” The project will develop important new methods that can be used to integrate data that emerge from smart cities (e.g. from traffic counters, social media activity, environment sensors, etc.) into largescale urban simulations in real time. Without the ability to integrate real-time data streams into models, 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 emergency evacuation. The successful applicant will join a team of PhD students, data scientists 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 how ‘big data’, that are generated in abundance in smart cities, can be used to improve the realism of simulations.
Funding and Eligibility
The project is fully funded! This includes:
– Tuition Fees
– Stipend (maintenance) ~£15,000 pa
– Research & Training grant: £750 pa
Total value: approx £84,000
The position is open to all UK/EU citizens. The following experience / training is required:
– A good undergraduate degree in computer
science, geography, mathematics, or a related
– Some experience in computer programming
For more information please contact the primary supervisor Nick Malleson.
Please click ‘more’ to view full details of the role and apply.More
Post Doc Opportunity
University Academic Fellow in Urban Analytics
Are you an academic with proven abilities to carry out research and teaching in topics related to Urban Analytics? Do you have an excellent emerging research record and proven success in obtaining funding? Are you passionate about delivering an exceptional student experience in a research-intensive international university? Do you aspire to become an academic leader in your field?
Cities have emerged as the dominant form of economic and social organisation at a global scale. The new science of urban analytics envisions step changes in the health, prosperity, welfare and quality of life of city inhabitants, through the extraction of value from new and emerging forms of data, and by the development and deployment of methods in artificial intelligence and data science.
The School of Geography at Leeds has established national leadership in Urban Analytics through RCUK recognition of the Consumer Data Research Centre (cdrc.ac.uk). Further investment from the University has allowed the establishment of the Leeds Institute for Data Analytics (LIDA) for the co-location and co-development of multidisciplinary research with real world impact. You will have the opportunity to develop international collaborations and relationships by working with scientists overseas at our partner Universities. This position will therefore provide outstanding new networks for an ambitious individual to deliver an exceptional programme of research innovation. You will also be a member of the School of Geography’s world leading Centre for Spatial Analysis and Policy (CSAP).
With a vision and drive to develop a prestigious internationally competitive research portfolio as well as a passion for undertaking research-led teaching you will make a significant impact on the performance, stature and profile of research and student education at Leeds. You will embark on a structured five year development programme, successful completion of which will lead to your appointment as a Grade 9 Associate Professor.
To explore the post further or for any queries you may have, please contact:
Professor Alison Heppenstall, Professor of Geocomputation
Dr Nick Malleson, Associate Professor in Geographical Information Science
Application deadline: Wednesday 31st October
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School of Law Opportunity
ESRC White Rose DTP Artificial Intelligence Studentship
Project: Exploring applications of AI for Monitoring and Detecting Changing Crime Problems
The nature and scope of crime is changing with the advent of new technologies that offer (1) new methods for committing existing crimes; (2) new opportunities for committing new types of crime; and (3) new means to prevent and detect crime. These changes present both significant challenges and opportunities to police and their crime reduction partners. This project will explore the application of AI techniques for detecting new crime problems in recorded crime data that is routinely collected by policing agencies but seldom analysed – with the aim of informing the development of early warning systems capable of targeting more effective service delivery.
Each year policing agencies and their partners collect increasingly large volumes of administrative data primarily for operational and housekeeping purposes. For a number of reasons these data are vastly underutilised in comparison to the collective investment in their capture. Moreover, the nature of police crime recording systems dictate that emerging trends in offending cannot be systematically identified without considerable work of a police analyst. Consequently, without means to automate strategic analyses of these data, important trends and patterns can be missed. In an attempt to bridge this significant analytical gap, this project will explore the effectiveness of several AI techniques in deriving actionable insights from largely untapped sources of police data.
To achieve this goal the project will apply AI methods to analyse a range of unstructured and semi-structured police recorded crime data with the aim of detecting new crime problems as they emerge.
The position is full time, with funding of £14,777. It is open to all UK/EU citizens.
Further information on the application procedure can be found here.
For more information on the project, please contact Dr Daniel Birks (email@example.com)
Closing date: 30th September 2018.More