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research oriented towards applications of quantum computing, quantum algorithms, or machine learning. Publishing articles in top-tier journals and disseminating results on thematic conferences. Applying
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advanced analytical and statistical techniques to extract actionable insights from complex datasets. Train, evaluate, and continuously refine deep learning and machine learning models, prioritising
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at the interface of biostatistics, machine learning, and biomedical data science. This mentored postdoctoral position is designed to support the development of an independent research trajectory in methodological
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Engineering, or related fields. They must have proven experience in the development and programming of Information Systems; prior experience in applications based on Data Analytics/Machine Learning and data
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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and modelling of omics, clinical and imaging data, development of reproducible pipelines, application of machine learning techniques, integration of multi-modal data, scientific publication and
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models remain a limiting factor in moving to a quantitative scale. Molecular simulation has benefited from recent advances in machine learning and generative artificial intelligence to such an extent
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Research and Imaging Centre (BRIC; https://www.plymouth.ac.uk/research/psychology/brain-research-and-imaging-centre ) . TARAs benefit from waived study fees and will work towards a PhD in an area of
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and the selected candidate will be expected to work onsite as of their effective start date. Applicants should be within a few months of completing their doctoral degree or hold a PhD in chemistry or in
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of senior researchers, the individual will help apply machine learning methods, with a focus on reinforcement learning, to mathematical problem solving. The role emphasizes hands-on experimentation