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Machine Learning, Human-Computing Interactions, Social Sciences, and Public Health. Applicants should hold, or be close to completion of, PhD/DPhil with research experience in computer science, statistics
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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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discipline (eg Statistics, Machine Learning, Biostatistics, AI, Engineering) with experience of developing and applying new methods. You will be able to develop research projects, with publications in peer
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via independent study and training courses. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics, computational biology, physics or a related discipline, and have experience
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essential that you hold a PhD/DPhil (or close to completion) in mathematics, computational biology, data science, statistics, physics, or a related discipline, and have experience of analysing and
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will have or be close to the completion of a PhD in Neuroscience, Psychology or a closely related discipline. With in-depth knowledge of cognitive and computational neuroscience including motivation
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team, and independently, are essential. You will also provide guidance to less experienced members of the research group, including postdocs, research assistants, technicians, plus PhD and project
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of the research group, including postdocs, research assistants, technicians, plus PhD and project students. You must have: A relevant PhD/DPhil (or be close to completion), together with relevant experience in
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach
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relevant skills acquired and will also be determined by the funding available. About you Applicants will hold a PhD/DPhil or be near completion of a PhD/DPhil in a subject relative to Structural Biology