174 assistant-professor-computer-science-data-"https:"-"https:" positions at Cardiff University
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part of an award-winning team, with competitive salary, Employee Assistance Programme and of course there's great benefits and discounts. Requirements This individual will have passion and enthusiasm
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the business units and within University IT. As a member of the IT Senior Leadership Team, the role acts as a strategic partner to the Chief Digital Information Officer, IT Director, Assistant Directors, and
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Advert Energy Officer An exciting opportunity has risen to join the growing Carbon Net Zero Team and help shape the sustainability performance of a world-class institution. The team is based
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the University and externally, such as funding bodies and DSA Assessment Centres, to help improve service levels. Gather and analyse data to update administrative systems with accurate information, establishing
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to relevant staff members, ensuring all relevant facts and information needed is recorded and passed on · Assist in the maintenance of routine records, updating databases as required, supporting
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Advert Research Technician Division of Infection and Immunity School of Medicine College of Biomedical and Life Sciences A Research Technician position funded by the Wellcome Trust is available in
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tools and test equipment. Assist and guide less experienced colleagues where necessary. Accept data, media, consumables and other items required for the processing of information and take responsibility
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one or more of the following techniquessc/snRNA-seq experimentation and data analysis Proteomic experimentation and data analysis Spatial biology techniques and data analysis Knowledge of the current
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and other groups, and using mixed methods to collect and analyse new data and synthesize existing data set. You will also help facilitate workshops in schools, and work alongside a Software Engineer to
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advanced computer modelling (in silico), through robot driven testing of implanted knees (in vitro), to 3-dimensional X-ray imaging of moving patients (in vivo) with Machine Learning driven analysis