550 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" "Univ" positions at University of Oxford
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genetic barcoding, clonal lineage tracing, and single-cell and spatial omics. The role involves analysing, interpreting and presenting experimental data, managing your own research and administrative
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over one or more core research thrusts within the lab’s multi-agent security programme. You should possess a PhD/DPhil completed, (or near completion), in theoretical computer science, information theory
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and day-to-day management of the LabCup inventory, risk assessment and asset management system across our laboratories. You will maintain accurate data on chemicals, equipment and risk assessments
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. The overall role of the post is to co-ordinate and participate in data collection and analysis that will help us fully understand how the socio-economic and demographic changes of the past half-century have
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administrative systems, and building strong working relationships across the Department and the wider University. Some responsibilities will involve highly confidential information and require discretion and sound
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Licence (PIL A, B & C) to conduct or assist with intracranial surgery in animal models. Assist with obtaining research data, such as immunocytochemistry and microscopy in brain tissue, molecular or chemical
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identification of phases in metallic systems such as aluminium alloys or steels. You will have demonstrated expertise in applying machine learning and computer vision techniques for the analysis of scientific
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events, familiarity with digital tools for managing datasets, workflows and reporting processes and the ability to support survey design and compliant data collection. The position is full time (part time
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areas of: microorganisms, insects, animals, plants, soils, or a combination thereof. Excellent interpersonal skills, the ability to work effectively in a team and to handle sensitive information
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situated in the Big Data Institute on the University’s Old Road Campus. NDPH contains world renowned population health research groups and provides an excellent environment for multi-disciplinary research