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Field
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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. The successful applicant will use state of the art inference algorithms to design, use and share the findings of epidemiological models that integrate across large and diverse datasets including capture-mark
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input needs, accompanied by a boost in algorithmic development, e.g., multi-modal learning, transfer learning, federate learning, and knowledge embedding, etc. However, a significant motivation of
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with MoniRail Ltd and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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in implementing, testing and validating complex minimisation algorithms that can be used for adaptive trials. Application & interview 8 Experience of collaborating on successful research proposals
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learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial analysis Strong publication record Experience in women and children’s
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range of computing subjects, including Cyber Security, Programming, Algorithms, Computer Logic and Architecture, Software Engineering, Database Design, both at undergraduate and postgraduate level
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subject area or subject specialism A4 Conversant in Python programming and deep learning algorithms for image analysis. For appointment at Grade 7: A5 Normally Scottish Credit and Qualification Framework level
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, applying and validating your algorithms through laboratory experiments. A PhD in Chemistry, Biology, Computer Science, or related fields with a focus on protein engineering. Proficiency in Python programming