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. There are opportunities to broaden out into other areas such as new algorithm development, and advanced computational methodologies for integrated analyses. You will have a key role in planning, designing and executing a
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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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web technologies Experience in teaching bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms
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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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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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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