Project: Detecting natural selection in bacterial genomic data
Davies Group
This project will use a wealth of pathogen genomic of group A Streptococcus spp. and Klebsiella pneumoniae to detect signatures of selection driving pathogenesis and drug resistance using computational methods. The data have are already available and have been curated, such that the project will focus on computational analyses. The student will learn bioinformatic genomics approaches and phylogenetic methods, and will develop skills in programming in Python and R.
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Davies Group
4 vacancies

The Davies group aims to apply genome sequencing methodologies and bioinformatics approaches to understand the evolution and transmission of bacterial pathogens. This knowledge can help facilitate a global understanding of pathogen evolution, in addition to informing public health intervention to reduce the disease burden associated with bacterial pathogens. Current projects address key research questions such as: is there a genetic difference between strains causing different disease manifestations? What is driving the emergence and dissemination of bacterial pathogens? Do host immune factors govern disease severity? Our research closely aligns with key international collaborators including the Wellcome Trust Sanger Institute in the United Kingdom.
Davies Group Current Projects
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Population genomics of endemic Streptococcus pyogenes
PhD/MPhil, Master of Biomedical Science, Honours
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Unravelling the drivers of group A streptococcal pandemics
PhD/MPhil, Master of Biomedical Science, Honours
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Detecting natural selection in bacterial genomic data
Master of Biomedical Science, Honours
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Real-time phylogenetics and epidemiology in SARS-CoV-2 genome data
PhD/MPhil, Master of Biomedical Science