Senior Research Associate in Modelling of Human Mobility and Social Networks

at  Lancaster University

Senior Research Associate in Modelling of Human Mobility and Social Networks
We are seeking a postdoctoral researcher with experience in infectious disease or network modelling to work on a collaborative grant between Lancaster University, Johns Hopkins University, University of Florida and Southampton University. The COVID-19 pandemic showed clearly that patterns of travel and interaction underpinned epidemic dynamics. This grant aims to expand our understanding of human mobility and interaction patterns, to improve infectious disease models and their ability to accurately predict the course of pandemics and epidemics.
The work will focus on several unique international travel and epidemiological datasets which span multiple spatial scales, combining information about social interactions, the locations in which they occur, and the attributes of individuals themselves. Data includes international flight data, and epidemiological data from China, USA and England. Analysis of this data will aim to understand and model the movement of individuals at both fine spatial scales, such as within a single city, as well as at a global scale. We expect the work to reveal the structure of social interaction and transmission networks, embedded within geographical and social space.
This post is based within Lancaster Medical School and the Department of Mathematics and Statistics at Lancaster University. The research is funded by an NIH grant, and the successful applicant will join an enthusiastic international team of leading researchers working on this project, led by Dr Amy Wesolowski (Johns Hopkins), Prof Derek Cummings (University of Florida), Prof Andy Tatum (University of Southampton) and Dr Jonathan Read (Lancaster University). There will be abundant opportunity to engage with this group and to travel between institutions. Further opportunity will be provided to engage in career development in research, leadership, and teaching skills. There is potential for the position to be extended, depending on funding.

Essential attributes:

• Experience in analysing epidemiological information
• Experience in handling large and complex data
• Knowledge of network science and/or mobility modelling
• An understanding of the principles of statistical inference
• Fluent in modern R or Python programming practice
• A strong record of publishing in peer-reviewed literature, appropriate to career stage
• Willingness to travel to work with grant collaborators and present at scientific conferences
• Strong team-working skills

Desired attributes:

• Experience in developing transmission models and fitting epidemic models to epidemiological data
• Experience in social network analysis and/or network modelling
• Knowledge of modern open-source code development

Informal enquiries to Dr Jonathan Read Jonathan.read@lancaster.ac.uk, Prof Chris Jewell c.jewell@lancaster.ac.uk, or Dr Jemma Kerns j.kerns@lancaster.ac.uk (Director of research, Lancaster Medical School)

Please refer the Job description for details