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. The closing date for applications is 12.00 noon on Thursday 30 October 2025 Informal enquiries may be addressed to Prof Amro Awad: amro.awad@eng.ox.ac.uk Further information can be found at http
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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | about 4 hours ago
the Safety and Surveillance group. Within a week of working here, your day could look like this: applying your epidemiological, statistical, data management and data analysis expertise to support public health
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internationally recognised for its research into the causes, mechanisms, and treatment of psychotic and affective disorders. The Department of Psychosis Sharing Data Initiative (DPSDI) is a strategic project aimed
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Datta and Dr Amrita Kulka in the successful execution of their Nuffield-Foundation-funded Big Data project “Towards housing affordability: local supply drivers and optimal policy” (project page here ). In
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, data analysis, and modelling. This role will focus on the development, implementation, and validation of advanced ML approaches for weed detection, discrimination, and management using complex biological
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of an ageing population. The postholder will support the programme through the application of a range of techniques and/or to collect and analyse data that enable the project to progress. This position involves
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April 2026 to 31 March 2027. The successful applicant will be responsible for data scraping and quantitative data analysis. The post will include data scraping of online content related to counter
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measure the impact of wood-aging on a range of foodstuffs. This portion of the project involves undertaking final validation experiments and refining the data analysis pipeline, before creating a final
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of Manchester and Imperial College. This role involves computational modelling and experimental data analysis, integrating mathematical models of clock neurons and populations with in-vitro and in-vivo
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Research Associate to support the work of Professor Angus Jones and the world leading Exeter diabetes research team. The successful applicant will work on a Diabetes UK funded project using data from >5000