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African partners funded by the Gates Foundation, which aims to make a breakthrough in the application of machine-learning forecasting methods for West African agriculture. The project is led by the UK’s
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patient safety. Our methods include: systematic literature reviews; qualitative, quantitative and mixed methods studies; complex intervention development; evaluation of interventions, including trials. We
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application of machine-learning forecasting methods for West African agriculture. The project is led by the UK’s Alan Turing Institute, with partners in Senegal and Ghana, and all partners will collaborate
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science, and a vivid interest on digital democracy, in particular, the areas of computational social choice (voting methods), deliberation and collective decision making. You will know how to work with data
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programme therefore it is anticipated that the successful candidate will have clinical academic expertise in geriatric medicine, and either a broad interest in ageing research methods or expertise in a
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statistical methods. We are committed to supporting and developing our team members, through attendance at conferences and access to training in research methods, and will support you to further develop your
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will join a team with a strong history of applied research in the areas of production and consumption. You will be required to use a range of both quantitative and qualitative research methods and apply
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architecture standards and methods. You will be responsible for the recruitment and retention of technical architecture resources, and represent the Technical Architecture practice in engagements within the IT
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timetabling needs, with an ability to negotiate effectively to mitigate competing demands across the institution, advising on resolution methods. You will be a source of expertise and guidance to staff and
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Data Compliance, Insights and Sharing (EDCIS) project. The EDCIS project focuses on enhancing the University’s current research information system (Symplectic Elements) and replacing the existing