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engineering? Then this professor position might be for you. We are looking for a new professor to lead research in probabilistic machine learning, with a focus on areas such as deep generative models, Bayesian
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multiple departments within the University of Cambridge as well as the collaborating organisations (RSBP, NIAB and UKCEH). The role holder will investigate machine-learning approaches that advance the core
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knowledge and proven capacity of data analytics and machine learning. *Excellent programming in Python, R, SQL. Have experience with tools such as Google analytics, AWS, Looker, Tableau, or similar
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on novel applications of machine learning techniques on mobility data towards resilient, safe, inclusive and sustainable urban micro-mobility systems. You will become member of an international, 38-partner
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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse
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to the stage of contracting the scholarship, and before that, they may be replaced by a declaration of honor. Preferential factors: • Expertise in Machine Learning; • Experience in developing machine learning
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adapters should be created and tested for previously selected detection methods, which can reliably bypass these detection methods. Be part of change Researching and implementing novel machine learning
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learning models on wearable electronic circuits, devices, and platforms, with particular emphasis on smart eyewear. The research activities will address multiple application domains, including embedded
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modelling, multimodal neuro-imaging and physics-informed machine learning to improve assessment of glioblastoma treatment response. The candidate will also be expected to contribute to the formulation and