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supports interdisciplinary research at the intersection of artificial intelligence (AI), machine learning (ML), high-performance computing (HPC), and applied scholarship. Reporting to the Provost Fellow for
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adaptive cybersecurity solutions for shared social and economic systems. The successful researcher will apply expertise in programmable networking, network traffic analysis, and machine-learning
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background in geomodelling, geophysical and geotechnical investigation, geomechanical engineering, and machine learning. You will be expected to work effectively on a geophysical/geomechanical project, to
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and machine learning algorithms to analyse and interpret the acquired data. The successful candidate will work primarily with Dr Qimei Zhang in the Department of Engineering at the Nottingham Trent
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Intelligence & Machine Learning Develop machine learning and AI models to identify, predict and characterise genome instability patterns. Design generative and predictive computational models to infer mutational
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within the Division of Artificial Medical Intelligence of Department of Ophthalmology in the University of Colorado School of Medicine. We focus broadly on quantitative and machine learning techniques in
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, that can be realised using cloud compute infrastructure and other novel deployment architectures. Given our team's existing research skillset in novel machine learning approaches, we are recruiting a
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will focus on efficient probabilistic analysis of high-dimensional and dynamic systems, including advanced sampling, surrogate modelling, and AI or machine-learning methods where appropriate. Key
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, epidemiology, biostatistics, machine learning or a closely related quantitative discipline. Strong knowledge of analytical methods relevant to epidemiological and biomedical research, including machine-learning
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. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals