102 structural-engineering "https:" "https:" "https:" "https:" "https:" "https:" "Multiple" Postdoctoral positions at University of Oxford
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We are seeking a full-time Postdoctoral Research Associate (PDRA) to join the Environmental and Biological Systems Engineering research group at the Department of Engineering Science (central Oxford
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. The group investigates both the fundamental properties of these proteins and their applications in biotechnology. A long-standing focus of the laboratory is the engineering of protein nanopores
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(PI), Saiful Islam, Peter Bruce), with UCL Chemical Engineering (Dr Rhod Jervis) and 4 industrial partners that brings together expertise in battery materials synthesis and device fabrication, advanced
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research and administrative activities. This involves small scale project management, to co-ordinate multiple aspects of work to meet deadlines. The post will be based in the Department of Chemistry
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testing for all three projects. Applicants should hold a relevant PhD/DPhil (or be close to completion) in engineering or a related discipline. Post-qualification research experience and a strong
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research project lead by Oxford Materials (Professors Robert House (PI), Saiful Islam, Peter Bruce), with UCL Chemical Engineering (Dr Rhod Jervis) and 4 industrial partners that brings together expertise in
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to develop a program of work investigating how brains use internal models of task and world structure to enable flexible goal-directed behaviour. The experiments will involve recording and/or manipulating
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, computational neuroscience, biomedical engineering, or a closely related quantitative STEM discipline. A strong background in cognitive, behavioural, and/or systems neuroscience, with relevance to learning
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, but is not required. You will be expected to manage your own academic research and administrative activities. This involves small scale project management, to co-ordinate multiple aspects of work
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to work within one of, or across, the four research themes: Learning with Structured & Geometric Models, Low Effective-dimensional Learning Models, Implicit Regularization, and Reinforcement Learning