We are seeking to appoint a Postdoctoral Scientist to work on the optimal design for community genomic surveillance of SARS-CoV-2 at local, national and international scales. You will be based at the Big Data Institute in Oxford, within the Nuffield Department of Medicine.

You will be responsible for developing working hypotheses with the support of the Group Leader and other members of the Virus Evolution and Pathogen Dynamics groups. You will develop new and adapt existing analysis methods and mathematical models to identify optimal surveillance strategies. You will be responsible for participating in the dissemination of this work via presentations at academic meetings and conferences, as well as preparing manuscripts for publication, including writing the first draft and preparing figures. You will also carry out collaborative projects with colleagues in partner institutions and other research groups, and also contribute and develop ideas for new research projects.

It is essential that you hold a PhD (or close to completion) in an appropriate research area, such as mathematical modelling, phylogenetics or statistics. You will have a keen interest in the research described here, and the aptitude to learn about SARS-CoV-2 biology, phylogenetics and methods to evaluate different strategies. It is essential that you have sufficient knowledge
so will have expertise in at least one programming language or mathematical platform. Previous experience of contributing to scientific publications or presentations is required, along with strong analytical and quantitative skills and excellent problem solving abilities. You will have the ability to lead a research project, to work collaboratively with others and to work to deadlines.

Applications for this vacancy are to be made online and you will be required to upload a supporting statement and CV as part of your online application. Your supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience.

This position is offered full time on a fixed term contract for 24 months and is funded by Li Ka Shing.
Only applications received before 12 midday on 17 November 2022 will be considered. Please quote 159756 on all correspondence.