利兹大学（University of Leeds）始建于1831年，坐落于英国第三大城市利兹市，世界百强综合研究型大学 。英国六所红砖大学之一，英国罗素大学集团创始成员之一，亦是白玫瑰大学联盟、N8大学联盟、RENKEI、中欧商校联盟、国际大学气候联盟、世界大学联盟成员，至今已培养出包括6位诺贝尔奖得主、3位国家元首和工党党魁基尔·斯塔默在内的众多著名校友。
Research Fellow in Infection Transmission Modelling (2 roles available)
Are you an enthusiastic and motivated researcher with an interest in developing models to understand environmental transmission of COVID-19?
Would you like to use your mathematical skills to understand risks and mitigations in workplaces or public transport? Are you interested in the opportunity to gain experience working in a cross-disciplinary team in collaboration with a range of partners?
We are currently recruiting mathematical modellers to work on simulating infection transmission on two projects:
TRACK project :
You will develop and use computational models of infection transmission in public transport settings as part of the EPSRC funded TRACK project.
This recently funded project across several universities and in collaboration with Defence Science and Technology Laboratory, Public Health England and Department for Transport aims to build robust models to evaluate COVID-19 transmission risks on public transport and determine the best mitigation strategies.
You will interact with people across the other work packages to incorporate data on virus survival, human behaviour and transport usage to develop risk planning tools that can be used by transport operators to plan mitigation strategies for bus and train networks in Leeds, Newcastle and London.
National Transmission project:
You will develop and apply computational models of infection transmission to a range of workplace and public settings as part of a UK government funded National Core Study to understand COVID-19 transmission.
You will be part of a core modelling team that includes researchers at Defence Science and Technology Laboratory, Health and Safety Executive and several universities, and will interact with research and stakeholder partners across a large multi-partner research programme including modelling, virology, epidemiology and outbreak investigation teams.
Both projects will involve developing Quantitative Microbial Risk Assessment (QMRA) based models that consider multiple transmission routes and the interaction of people.
These will be applied to a range of scenarios to understand the risk factors for transmission and the potential for mitigation measures.
You will hold a PhD (or be close to completion) or have equivalent experience in a relevant engineering or science discipline, with strong experience of developing and applying computational simulations.
To explore the post further or for any queries you may have, please contact:
Dr Martin Lopez-Garcia, Lecturer, School of Mathematics.
Professor Cath Noakes, Professor of Environmental Engineering for Buildings, School of Civil Engineering.