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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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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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offers significant opportunities for growth and development as an academic. About You You will have a degree in a relevant subject (including, but not limited to, data science, statistics, computer science
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data from a variety of sources, including Spatial Transcriptomics and multiplex Spatial Proteomics platforms and developing skills in computational biology and mathematical spatial analysis via
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research in the area of mathematical and computational modelling of materials in the Department of Materials. The post-holder will be expected to lead a research activity within the general area of materials
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Leedham and Professor Helen Byrne at the Mathematical Institute University of Oxford. You will work as part of the Oxford Spatial Biology Group, a large multidisciplinary team of mathematicians
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NDPH Fellowship programme is intended to support suitably experienced individuals to develop an independent research area which will enhance Population Health research in Oxford. Under the guidance
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qualification in bioinformatics, computational biology, biostatistics, applied mathematics, or related discipline, and have demonstrable experience in handling and analysing various types of ‘omics data types
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The Oxford Applied and Theoretical Machine Learning group at the Department of Computer Science has a new opening for a Project Support Officer, working together with Professor Yarin Gal. In
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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will