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of leading transformational change and embedding a culture of innovation across large, diverse organisations. You should have proven experience in attracting and managing diverse sources of funding
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of programme tools, including Wrike (our project management platform) • Drive continuous improvement in project delivery processes About You • Strong experience in PMO leadership within large and complex
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of parasite material. Parasite material, including all developmental stages of Schistosoma spp, is used to generate large scale bulk and single cell omic databases and validate data-generated hypothesis. We
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research environment bridging molecular biology, genomics, and computational data science, the post focuses on integrating enhancer biology with large-scale synthetic biology and single-cell multiomic
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the department at Divisional and University HR networks and working groups. The Department of Experimental Psychology is a large, internationally recognised department with a high volume of academic activity and a
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). The successful applicant will be responsible for the day-to-day management and administrative support for a large portfolio of research studies, studentships and fellowships funded through the National Institute
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(University of Cambridge). This post will be based at the Oxford Centre for Integrative Neuroimaging (OxCIN), Oxford. In this grant we will triangulate large-scale case-control data on developmentally informed
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large, internationally recognised department with a high volume of academic activity and a fast-paced, research-driven culture. We are collaborative, friendly and ambitious, with a strong commitment to
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information that Oxford students need to thrive in their academic and personal lives, and relies on effective communications to achieve its goals. The Communications Officer will contribute to the division’s
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, including P11Ds and Pay As You Earn Settlement Agreement (PSA) records. The role also involves overseeing a range of processes involving the maintenance of large volumes of varied and often complex data