Research Fellow in Real-Time Agent-Based Modelling
University of Leeds
You will work on a project, funded by the European Research Council, called Data Assimilation for Agent-Based Models (DUST). The ultimate aim of the project is to develop an agent-based computer simulation that can be used to model social phenomena – such as disease spread, traffic congestion, or crowding in busy public places – in real-time, providing valuable information to decision makers. Agent-based modelling is an ideal methodology for this type of simulation but has rarely been used to make real-time predictions. Hence there is an opportunity to develop models that areable to incorporate real-time datato make their short-term predictions more accurate. The project will attempt to combine cutting-edge methods in data assimilation with agent-based modelling to create accurate, real-time models for use when rapid decision making on the best available evidence is required.
The research team is lead by Dr Nick Malleson and will be located within the Leeds Institute for Data Analytics (LIDA), which is emerging as an international centre of excellence in agent-based modelling. The city of Leeds is already recognised as a hub for big data analytics in business, health care and academic research. In addition, the University is a partner in the Alan Turing Institute, which is the UK’s national institute for artificial intelligence and data science, offering exciting opportunities for LIDA researchers to engage with scientific leaders from a range of fields.
You should have a PhD (or be very close to obtaining a PhD) in Geography, Computer Science, Mathematics, Statistics, Physics – or a related discipline with a significant component of programming and/or data science – and be able to demonstrate a combination of enthusiasm and expertise in computational modelling and data analysis. Direct experience in developing and using agent- based models is not compulsory.
Further information on the project and the Leeds Institute for Data Analytics (LIDA) can be found on the Additional Information sheet.
To explore the post further or for any queries you may have, please contact:
Professor Nick Malleson
Tel: +44 (0)113 343 5248, email: firstname.lastname@example.org