13 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" positions at University of Manchester in United Kingdom
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University of Manchester The University of Manchester (www.manchester.ac.uk) enjoys a global reputation for its research and its innovative approach to learning, with an on-going £1 billion investment in
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About the Role: At the University of Manchester, our legacy is built on a history of progression, and a pioneering spirit. As the birthplace of the first stored program computer, the first modern
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inference, and Machine Learning methods. In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group, as
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candidates will have specialist knowledge in signal processing and algorithm design, with experience in machine learning, AI system development and reinforcement learning along with a strong publication record
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Spiders” awarded to the Computer Science Department of the University of Manchester, see https://www.renaissancephilanthropy.org/learning-to-do-math-with-vampires-and-spiders The formal methods group
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(NLP) and machine learning to analyse text data. For this project the research associate will be based at the Centre for Musculoskeletal Research (CfMR), Centre for Epidemiology, The University
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candidate with a strong background in some aspect of numerical analysis for PDEs and an interest in scientific machine learning and probabilistic methods, who enjoys working in collaborative inter
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Associates and PhD students. We are particularly interested in candidates who bring expertise at the intersection of artificial intelligence, machine learning, and criminology. The successful candidate will
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We are seeking a Research Associate with expertise in machine learning and causal inference to join the University of Manchester spoke of “CHAI hub: Causality in Healthcare and AI”. The CHAI hub
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and materials engineering. They will do this by integrating modern data-centric approaches, such as physics-informed machine learning, structure-aware modelling, and digital-twin methodologies, with