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Field
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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testing of machine learning/AI algorithms Integration of radiomic and biological datasets Working closely with Medical Physics colleagues on reviewing recommendations for detection of specific metabolites
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as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas
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Radio Frequency (RF) Systems: Extensive knowledge on network management and control Software Defined Radio (SDR): Data Analysis and Processing Programming and Software Development AI/Machine Learning (AI
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challenges from low carbon shipping and sustainable fuels to solar power technologies and advanced brain models. Learn more at https://mecheng.ucl.ac.uk . Within this dynamic environment, the Moazen Lab is
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Programming and Software Development AI/Machine Learning (AI/ML): Research and Publication Additional information For informal queries, please contact: Professor Dimitra Simeonidou: Dimitra.Simeonidou
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engineering, including machine learning, sustainable construction, climate adaptation, and intelligent tools. Demonstrate future contributions to capacity-building and socio-economic advancement after
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proven interest in AI foundations and its application in civil and environmental engineering, including machine learning, sustainable construction, climate adaptation, and intelligent tools. Demonstrate
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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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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