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. These workflows will then be applied in relevant Saudi Arabian contexts to help discover new ore deposits. The position will combine techniques from geological modelling, geostatistics, machine learning, and
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modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
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(Research Assistant) or PhD degree (Research Associate) in computer science or a related area or equivalent experience. Familiarity with standard machine learning libraries/data analysis, specifically as
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Professor Fei Lu and Bloomberg Distinguished Professor Mauro Maggioni on topics including mathematical foundations of data science and statistical/machine learning, with an emphasis on inverse problems and in
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that apply: ☒Sitting at computer work station for long periods of time ☒Standing for long periods of time ☒Risk of back injury from moving/lifting, equipment, or materials ☐Repetitive motion ☒Lifting/Carrying
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will hold a PhD (or close to completion) or possess equivalent research experience in a relevant computational field such as data science, artificial intelligence, machine learning, computer science
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interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Christopher Summerfield. The post-holder will have responsibility
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Engineering, or a closely related field. * Proficiency in MATLAB or Python. * Prior experience with Neuroimaging analysis (using FSL, AFNI, SPM, etc.) * At least one journal publication as first author
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to work on the discovery of new superconducting materials with high critical temperatures, using novel methods and concepts such as machine learning and quantum geometry. The project is related to large
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astrophysics, exotic core-collapse supernovae, and machine learning methods for time series analysis. A PhD in Physics, Astronomy, or a closely related field is required. The position will entail work on a