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and user support for the Collections Management System (EMu) used by the Museum of Natural History and the History of Science Museum. You will maintain, develop and implement data standards, policies
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, and the successful applicant’s work will establish a method to add new dimensionality to cryoEM data using specimen potential maps. You will develop methods to detect potential gradients in cryogenic
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with examinations and teaching events. Acting as a key point of contact for students and staff, the role also involves managing shared inboxes, communicating important information, maintaining accurate
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collation, analysis and presentation of both large-scale survey data, as well as extensive qualitative data. The successful candidate will work closely with the lead researchers and UEFA. The role requires
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, conditions and benefits , including development opportunities, health and wellbeing support and a work-life balance. For more information, please do get in touch by email with Dr Connor Darling, , kindly quote
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and funding, particularly incorporating policy objectives within processes, while considering the level of institutional burden and monitoring information required. This will include: contribute
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recruitment journey. This position ensures accurate data management, efficient application processing, and effective communication strategies to drive engagement and conversion. The role will be based
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responsibilities will include: Working collaboratively with colleagues and stakeholders to collate and process large quantities of data and translate this into the FAS academic timetable, ensuring that services
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logical approach to tasks High standard of written and verbal communication Ability to manage confidential and sensitive information with tact and discretion Confidence in working collaboratively with a
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on the study of the digital traces we left behind to capture human behaviour and social dynamics through the lens of Network Science, Complexity Theory, and Data Science. The team is made up of researchers in