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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon
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, to discuss the project or if you have any questions. Entry requirements: Applicants should have, or expect to achieve, at least a 2:1 bachelor’s degree (or equivalent) in biomechanics, sport science
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and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National Physics
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microbiome and welfare of retired racehorses (randomised controlled trial). This project will provide the scholar with training and experience in animal welfare assessment, microbiome science and advanced
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of bioinformatics, biology, or related fields - M.Sc. is required. Key qualifications and qualities include: Experience in bioinformatics/computational biology; experience in protein structure prediction is
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing
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degrees in either the natural sciences (chemistry, physics, mathematical/computational biology) or in the formal sciences (statistics, computer science, mathematics), but must have a serious interest in
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fundamental science to social science; policy-makers, regulatory bodies; industry, patients and citizens) and PhD candidate will also join these efforts. As a PhD candidate, you are committed to conducting
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Job Description We invite applications for a fully funded 3-year PhD position in the Embedded Systems Engineering (ESE) research section at DTU Compute in collaboration with the Technical
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members of staff. Research in the Department is organised into six themes : Causality; Computational Statistics and Machine Learning; Economics, Finance and Business; Environmental Statistics; Probability