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to small animal patients receiving specialist care in the small animal hospital. D2 Understanding and experience of statistics, databases and other IT applications/packages. Experience Essential: E1 Clinical
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upon genetic results. Techniques used: you will be trained in a large variety of techniques including epidemiology, statistical genetics, in silico data mining, cell culture including CRISPR-based genome
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. Conduct statistical analyses and predictive modelling to support P&OD initiatives and identify potential risks or improvement opportunities. 5. Participate in P&OD projects and initiatives related
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to recognise the shape, size, and materials of urban features, through the application of statistical, machine learning (ML) and artificial intelligence (AI) techniques. The use of freely accessible raw GNSS
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health, statistics, epidemiology, or behavioural sciences to join our group of PhD students. Methods will include: Secondary Analysis of big data using natural experimental approaches; Qualitative Research
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geographical scales, by applying state-of-the-art statistical techniques, such as the Integrated Nested Laplace Approximation (INLA). Furthermore, the student will gain experience in the management and
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in the School of Mathematics and Statistics, where research on Foundational AI is being actively pursued. Purely as a guide, candidates might typically have published in conferences such as ICML
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Our Doctoral Training Programme focuses on training PhD students in key MRC skills priorities in quantitative skills (mathematics, statistics, computation, and developing digital excellence) as
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returns, for example, the annual Higher Education Statistics Agency (HESA) Finance Return, the annual Knowledge Exchange (KE) Return, the annual Higher Education – Business and Community Interaction Return
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the institutes. A variety of approaches are used, including ecology, epidemiology, mathematical, computational and statistical modelling, bioinformatics, parasitology, immunology and polyomics (genomics