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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, University of Oxford. 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...
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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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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
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, and maintaining software systems to support these research projects. This includes building data pipelines, developing algorithms, and ensuring that data is stored efficiently and is accessible to all
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type (iv) work with the computational biology team to transfer this information into a AI algorithm that can distinguish neurodegenerative and neuroprotective phenotypes (v) work with colleagues in
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developing data analysis approaches and contribute to the overall study design and implementation. In particular, this will involve applying existing or even developing new algorithmic approaches for TAPS data
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Trust and is fixed-term for three years. This research position aims to develop machine learning algorithms to enable learning human ethical values from survey data. The postdoctoral researcher will
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developed goal-sequence generalization task. The project will integrate high-density silicon probe recordings, optogenetics, pharmacology and advanced computational tools to analyse neural algorithms