70 condition-monitoring-machine-learning Postdoctoral positions at University of Oxford
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, genetics or other related discipline, and have experience of the genetic/molecular analysis of human diseases, such as cancer. You will be able to work with a high degree of independence, to learn rapidly
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of Physics offer an inclusive and diverse environment and workplace. We strongly encourage applications from all backgrounds and genders to apply. The post-holder will have the opportunity to teach. Please
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sufficient specialist knowledge in the discipline to work within established research programmes. You will have the ability and desire to learn and understand new experimental techniques, and to conduct
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in Python, or demonstrated ability to rapidly acquire fluent knowledge of new programming languages, libraries, and platforms. A background and/or interest in mathematics or computer science would be
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demonstrated ability to analyse and interpret complex multidimensional data. Experience of programming in Python, or demonstrated ability to rapidly acquire fluent knowledge of new programming languages
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develop photoluminescence and spin control capabilities, under cryogenic conditions, to probe the defects’ electronic structure and spin properties. This effort will be combined with ongoing work in the
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to unravel the molecular mechanisms behind these aging-related phenotypes. A willingness to learn and employ biochemical approaches and interact with external collaborators in molecular biology and
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analyze the resulting datasets using biophysical modelling. A willingness to learn and employ biochemical approaches and interact with external collaborators in molecular biology and biochemistry
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academic centres throughout the UK. The post will include the opportunity to work with experts in depression, learn about clinical management of patients with depression (their assessment, treatment) and to
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should be an expert in at least one of those techniques and keen to learn the others. You also should have a deep interest in molecular mechanisms underlying biological processes and – if not experience