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Evaluating the use of longitudinal over-the-counter healthcare sales data as a source of syndromic surveillance for community-based infections UK Health Security Agency and Nottingham University
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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questions for research interviews. Conducting a series of semi-structured interviews at UoN. Transcription and analysis of qualitative data. Attending research team meetings. Contributing to publication
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. Adults discharged following a hospitalisation episode for community acquired pneumonia will be randomised to receive either standard of care (which includes a patient information sheet) or standard
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analyses by age, ethnicity, and index of multiple deprivation will be performed. The second stage of the study will involve the analysis of prospectively collected EQ-5D-5L data from a cohort of patients to
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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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platform. Training the development digital-twin using real-time data from hardware available Electrical power level studies with developed digital twin to identify visible solutions for distribution electric
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-edge advancements in automated drug discovery through the integration of high data-density reaction/bioanalysis techniques, organic synthesis, laboratory automation & robotics and machine learning
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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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the PhD. The Faculty has outstanding facilities and works in partnership with leading industrial partners. Please contact Mohammad Reza Ilkhani ezzmi1@exmail.nottingham.ac.uk for further information and an