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state-of-the art polymer synthesis platforms which can generate libraries of new polymers. These systems include sophisticated machine learning guided reactor platforms which integrate experiment
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. Ability to work both independently and as part of a multidisciplinary team 6. Willingness to learn new analytical methods within the Machine learning field Desirable criteria 1. Completed PhD with
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education courses at the postgraduate level. They will support the planning, organisation and delivery of teaching at the Defence Studies Department. Successful applicants will teach and supervise students
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, organisation and delivery of teaching at the Defence Studies Department. Successful applicants will teach and supervise students who are serving officers or civil servants in the UK and allied armed forces
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in Shrivenham, will undertake high-quality research and support a range of professional military education courses at the postgraduate level. Successful applicants will teach and supervise students
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Computer Science or near completion. Higher language computer programming (python) General machine learning experience (vision, structured data, NLP) Machine learning libraries (SciKit Learn, pytorch,…) Scientific
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Electronics, Machines and Drives Research Group (PEMC) at the University of Nottingham. The PEMC research group has grown exponentially and now has over 200 members, 24 academics and circa 130 PhD students
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criteria Publications in academic journals Experience of mentoring junior researchers Experience of pharmaco-epidemiology or drug safety research Experience in AI/machine learning Experience in dermatology
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computer programming (python) General machine learning experience (vision, structured data, NLP) Machine learning libraries (SciKit Learn, pytorch,…) Scientific / Medical Writing Ability to work calmly under
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Associate with understanding of neural signal processing and a passion for AI/machine learning to assist in advancing approaches to analysis, classification and decoding of high-resolution