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computational analyses of epigenomic/transcriptomic data and machine learning. Experience in single-cell omics data is desirable. The post holder will be responsible to develop pipelines for the analysis
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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based
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” which examines signal processing and machine learning methods for inferring active travel activities from optical fibre signals. About You Applicants must have an Undergraduate Degree in Computer Science
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-edge machine learning techniques will be used, including Large Language Models (LLMs). About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the
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the areas: AI, deep neural networks, machine learning, applied topology, probability, statistics, signal processing. About the School The School has an exceptionally strong research presence across
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have expertise in data and statistical analysis with a strong component in machine learning and artificial intelligence techniques. You will have programming skills in R, Python or equivalent language
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relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning techniques, and
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The University of London The University of London is the UK’s largest provider of international distance and online learning and the convenor of a federation of 17 London-based universities, many
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education strategy across seven departments and multiple LSHTM-based centres, with a focus on building and strengthening skills in artificial intelligence and machine learning for epidemiological research
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machine learning and deep learning frameworks, development of API’s and dashboards alongside proficiency in programming skills, will stand you out from your peers. For all our roles we are searching