The genomic revolution is enabling the generation of different kinds of omics datasets from not only high quality biological materials, but more unusual sources including historic and archaeological remains. Indeed, with the availability of such a varied set of data has brought the need for methods to use these data to draw biological inferences. The major challenge is how to analyse and integrate such datasets, especially at the population level. In this regard, your position would be working alongside the research group of Assoc Prof Shyam Gopalakrishnan, on the development of new methods in population genomics, statistical genomics, metagenomics and multi-omics data integration. The focus of the position will be to develop new statistical and machine learning methods to integrate relevant data from these areas into an Evolutionary Biological framework. Subsequently, you would apply such tools to understand the role of microbiomes and host-microbiome interactions in evolutionary biological questions including speciation, domestication, and adaptation.
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