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Applications are invited for a University Assistant Professorship in the broad area of Machine Learning. The successful candidate will join the Computational and Biological Learning Lab (CBL
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interactions in the condensed phase and at surfaces, with a particular emphasis on the development and application of first principles and/or machine learning approaches. Research in the Michaelides group
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models and machine learning algorithms. These methods will be merged to support the derivation of an analytical equation for water table depth estimation. The ideal candidate will have experience in image
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clusters, biophysics, solids and surfaces, machine learning, quantum computing, and self-consistent fields. We develop new theory and associated computational tools, which are supported and distributed
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Commitment Action Plan - a sector-wide initiative. About Learning and Development (L&D): Our L&D team is dedicated to supporting excellence in learning, teaching, and research at the University of Cambridge
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Transactions on Probabilistic Machine Learning. A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, L Kennedy, J Gabry, PC Bürkner, M Modrák (2020). Bayesian Workflow. B Carpenter, A Gelman, MD
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relevant field (e.g. NLP, AI, Machine Learning) and be able to demonstrate active, collegial engagement in teaching, research, and administration, commensurate with their stage of career. The candidate will
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willingness to learn. Duties will include daily checks of plant equipment, general maintenance, minor redecoration, fire safety testing and porterage. You will be part of our growing Building Services team, and
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. The successful applicant will have the opportunity to develop skills in mathematical modelling, advanced numerical simulations and machine learning. Fully involved in the basic research in these areas whilst also
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through