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The Gambia who will work remotely with Prof Kat Holt’s team (see holtlab.net) to investigate transmission of Klebsiella pneumoniae in neonatal units in Africa using genomic epidemiology. The successful
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with a global sediment database and use remotely sensed and other geographical data with machine learning/Bayesian Modelling techniques to establish drivers of global sediment flux. They will use
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engineering and/or programming and/or algorithm deployment within the aviation sector covering intelligent sensing and acquisition and knowledge of data communication and data management of aircraft systems
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remote sensing and machine learning, and you will gather in-situ field data to verify the forecast. For ARISE and MS4S you will develop hydro- and morpho-dynamic models to predict coastal sediment
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remote (home) working and some office hours by agreement. Please note a full application including a covering letter detailing your experience alongside a CV is required for applications to be considered
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ideally have knowledge in marine remote sensing, radar operations, an in depth understanding of coastal wave and current physics. Strong programming and data analysis skills are desired along with practical