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reasoning. You will be an experienced prescriber and have practical teaching experience underpinned by postgraduate education, with familiarity with face-to-face learning - including assessment - as
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of 160 hours. There will be opportunities for professional development, including networking opportunities to learn from others working in this area from across the sector. This is a three year
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Project Overview This project is at the intersection of machine learning, differential equations, and numerical weather prediction (NWP). This collaboration with the Met Office integrates advanced
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the expertise and flexibility to teach a broad range of topics in Mechanical Engineering with a focus on Mathematics to Undergraduate students. You will be expected to design and deliver high quality teaching of
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for someone with a PhD in Sports Science, Data Science or Computer Science with expertise in machine learning, data analytics, and signal processing. It is not necessary to have detailed knowledge of rugby, but
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will initially be focused on developing and evaluating machine learning and statistical modelling tools to predict and classify disease trajectories using large scale health records databases to answer
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record keeping are crucial. We work together as a team to achieve overall results and you will need to be a good team player. An interest in learning about and working with engineering and design subject