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equivalent level of professional qualifications and experience, with expertise in at least one of the areas: machine learning, applied topology, and/or probability theory. About the School The School has
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areas: machine learning, applied topology, and/or probability theory. About the School The School has an exceptionally strong research presence across the spectrum of Mathematical Sciences. It is part of
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Overview About the Role Applications are invited for a motivated and committed Machine Learning Engineer. The successful candidate will contribute to Queen Mary’s national reputation for research by planning
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computing, AI, biomedical engineering or signal processing) or a higher degree (e.g. MSc) with substantial experience in multimodal machine learning with appropriate track record. Excellent programming skills
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Telescope. This research may involve the analysis of large datasets, the generation of new simulations and the utilisation of Machine Learning techniques. The PDRA will be expected to hold a PhD in
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computer science with specialisation in data science, machine learning or deep learning, or in Earth/Environmental Science with experience in applied data science, machine learning or deep learning. You also will
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London. One focus of the Centre is to apply epidemiological and machine learning approaches to large-scale studies that have cardiac imaging available, such as UK Biobank, Study of Health in Pomerania
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Bayesian networks, causal discovery/machine learning, Markov decision processes, decision theory, simulation Applicants are expected to broaden their knowledge in autonomous electromagnetic defence systems
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have a PhD in a numerate field with expertise in machine and deep learning methods, supported by high quality publications. Experience of applying such methods to healthcare data is an advantage
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at the PDRA level must have a PhD in Computer Science or a related field. Candidates must have substantial knowledge in Deep/Machine Learning, Large Language Models (LLMs) Natural Language Processing and