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We seek a talented and insightful postdoctoral scientist to develop new theoretical approaches for tracking transmission during emerging epidemics. We are looking for someone who has both strong theoretical skills and an applied, goal-orientated approach to problem solving.
We aim to build new analytical frameworks that can combine multiple heterogeneous sources of data about disease transmission. The theoretical nature of this work means that previous experience in the fields of infectious disease modelling, evolutionary analysis, or computational cartography is not essential. However, the candidate must have a strong interest in building solutions for these disciplines, and will be expected to learn the conceptual bases of them. The project is expected to explore a wide range of concepts and techniques, e.g. stochastic birth-death and branching processes, graph/network theory, algorithmics, computational statistics, and multi-scale dynamic modelling.
The candidate will work with Professor Oliver Pybus in the Department of Zoology and join the Oxford Martin School Programme on Pandemic Genomics (http://bit.ly/2HrWPfD). Within this team, the candidate will lead the development of new mathematical representations of epidemic dynamics that can abstract and unify disparate data sources. Once this development work is complete, the candidate will work with other team members to test the new framework, and begin its computational implementation.
Candidates must have strong quantitative skills and a PhD in a relevant discipline. We welcome applications from candidates with PhDs in quantitative biology, mathematics, statistics, physics, engineering, or computer science.
This is a full-time fixed-term post for 3 years.
Applications for this vacancy are to be made online. You will be required to upload a CV and a supporting statement as part of your online application.
The closing date for this position is 12.00 noon on 28 March 2018.
Apply now: https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.d...
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