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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing
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programme as part of the collaborative NINEDTP. The Department’s research strategy is built around five themes: Communities and Social Justice; Health and Social Theory; Higher Education and Social
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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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at the University of Liverpool. You will be part of an exciting Liverpool-based UKRI-funded programme of research called ¿SCHOUSE: Supporting Communities in social Housing and Optimising Urban food System
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spectroscopy Experience Proven experience in algorithm development to do physiological signal processing Experience in advanced computational techniques to assess and enhance signal quality Experience in machine
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing
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including discounted membership for our state of the art sport and gym facilities and access to a 24-7 Employee Assistance Programme. • On site nursery is available plus access to holiday camps
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students and over 500 Single Honours undergraduate students. We offer a 3-year BSc degree programme in Biological Sciences and a 4-year MBiol, while also contributing to Natural Sciences. We also run a PGT
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cytometry will be an advantage. The project has a major computational component both for AI-driven modelling and predictions, and for bioinformatics analyses of wet-lab data. This will be performed by