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Project

Application and visualisation design for Bayesian phylodynamic inference

The first part of the project will involve becoming familiar with Bayesian phylogeographic reconstructions on various pathogens, but with an initial focus on SARS-CoV-2 Lineage B.1.525. While a previously hired PhD student will focus on developing novel models for phylogeographic inference, applying these models and comparing their inference results to one another constitutes an important responsibility within the current job description. A collection of useful data sets from different geographic regions will have to be established, and this for different pathogens, and will need to be carefully analysed alongside available metadata and current hypotheses on viral spread within the field of research. In the second part of the project, useful software applications that complement Bayesian phylogenetic and phylodynamic inference will need to be designed and implemented. In order to translate the phylodynamic output of our proposed models into tangible responses, the goal will be to develop a user-friendly, feature-rich, interactive and flexible web-based visualization platform that can easily be applied to different pathogens and enables sharing these visualisations as frictionlessly as possible. The web technology platforms to be used are not carved in stone and can be chosen provided they scale well with increasing amounts of data.

Date:1 Dec 2021 →  Today
Keywords:Bayesian phylodynamic inference
Disciplines:Bio-informatics
Project type:PhD project