90 phd-position-computer-science-"IMPRS-ML"-"IMPRS-ML" positions at University of Leeds
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the programme. Leeds has a longstanding and highly regarded clinical psychology training programme. We are a close knit, friendly and supportive team, with excellent links with clinical psychology and expert by
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Science to teach on, enhance and develop a range of taught postgraduate and undergraduate programmes focusing on data science applications in the music industry. You will possess a postgraduate degree and
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care professionals, independent sector health and care providers, patients and the public and other NIHR customers including Life Sciences Industry. You will be responsible for leading the operational
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Research Assistant in Cell Biology and Imaging, Faculty of Biological Sciences Salary: Grade 6 (£32,546 - £38,249p.a.) This role will be based on the university campus. We are also open to
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You will contribute to a programme of research, funded by the Horne Family Charitable Trust, which aims to increase the evidence base on Domestic Violence and Abuse (DVA) experiences of people with
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have a PhD or be a PhD candidate who has already submitted your thesis prior to starting the position, with a research track record on artificial intelligence, data science and computational social
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clinicians? We are looking for a proactive individual to join our Science and Technology Of Robotics in Medicine (STORM) Lab (https://www.stormlabuk.com/ ), bringing their excitement for scientific research in
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education offerings? The University of Leeds Strategic Plan (2020-2030) sets out an ambition to place the University at the heart of a global network, finding innovative solutions to regional, national, and
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Universities? You will join a collaborative programme with Merck Electronics KGa, a world-leading company working in liquid crystals. You will work with a team of scientists from the company along with Dr
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project meetings. You will have a PhD in atmospheric science or climate science, including experience of running and analysing numerical models, and an appreciation of machine learning methods suitable