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We are seeking a Research Assistant for a project testing the ability of phage to target bacteria carrying plasmids associated with antibiotic resistance genes. Many of the most important antibiotic resistance genes are carried by conjugative plasmids that transfer resistance across strain and...
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We are currently seeking a Postdoctoral Research Associate to join our dynamic group at the Department of Biology. The Verd lab is interested in the diversity of biological form, how it is generated and how it evolves. In particular we focus on the evolution and evolvability of vertebral counts,...
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project to develop a systematic framework for reconstructing the evolutionary histories of pathogens. The role involves using viral sequence data and models of sequence evolution to investigate both
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accessibility of the method to enhance user ability to perform analyses in comparative genomics, enable new analyses, and gain new evolutionary insights from data generated using OrthoFinder. The successful
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. The postholder will help lead a project work package
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and breeding grounds for whales in the past. Using phylogenetic comparative methods and the niche modelling results, the post holder will examine the evolutionary history of ecological niches broadly
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aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will support the development
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and evaluation. The post holder will take a leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods