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Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant. an accredited Disability Confident Leader ; autism friendly university , committed to building disability confidence and
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modelling, satellite data assimilation, multivariate statistics, and machine learning. Prior experience with model and satellite products for mapping and understanding SM-dependent hazards (like floods
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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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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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UKESM1 or similar models, advanced data analysis and machine learning, would be advantageous. Grade E: You will be near completion of a relevant PhD or have equivalent research experience, and be able
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developing and implementing machine learning/AI solutions using relevant languages and frameworks Excellent communication skills and proven ability to collaborate with diverse stakeholders Technology and
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: Genomics, precision medicine, bioengineering, and health data science AI and Digital: Machine learning, robotics, digital health, and cybersecurity Defence and Advanced Manufacturing: Secure systems
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relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning techniques, and
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field (with a CGPA of at least 3/5) Experience (e.g. coursework, projects, etc.) in AI and machine learning, including understanding of various DNN architectures, training models, and applying them
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Theory and Machine Learning, can easily integrate into our team, independently contribute to current research, and work with responsibility for results. The research project is a collaboration between the