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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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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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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
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of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain
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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches
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fundamental algorithms for producing policies for rich goal structures in MDPs (e.g. risk, temporal logic, or probabilistic objectives), and modelling robot decision problems using MDPs (e.g. human-robot
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machine learning methods to improve the understanding, treatment and prevention of human disease. The successful candidate will develop novel statistical and machine learning algorithms to address key