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Statistics at the University of Glasgow. This project is funded by the Engineering and Physical Sciences Research Council (EPSRC) and is available for a period of 30 months. The successful candidate will also
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Scottish Credit and Qualification Framework level 12 (PhD) or alternatively possess the equivalent in professional qualifications and experience, with experience of personal development in a similar or
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change. The postholder will be based at the School of Mathematics and Statistics, University of Glasgow working with Prof Christina Cobbold and will work jointly with project partners Drs Steven White and
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line with the University’s Strategic Plan, World Changers Together. Qualifications Essential A1. Normally Scottish Credit and Qualification Framework level 12 (PhD) or alternatively possess
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equivalent A2 A comprehensive and up-to-date knowledge of the wider subject area or subject specialism Desirable: B1 An awarded [or recently submitted or near completion] PhD in subject specialism or
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of specific virus resources in line with CVR research priorities. The post is suited to a highly motivated individual with a keen interest in virus research and with relevant experience, and/or Masters or PhD
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statistics, as well as substantiated knowledge of machine-learning and Artificial Intelligence (AI) methods applied to Earth Observation geospatial data (e.g., satellite imagery, sensors, street view images
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completion) PhD in subject specialism or equivalent Knowledge and Skills Essential: C1 Knowledge of a variety of modelling techniques from statistics, machine learning, or related disciplines, including
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the format explained below you will not be shortlisted for interview. Qualifications Essential: A1 PhD in Virology or other relevant subject, or alternatively possess the equivalent in professional
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. Knowledge, Qualifications, Skills and Experience Knowledge/Qualifications Essential: A1. Scottish Credit and Qualification Framework level 11 or 12 (Post Graduate or PhD Qualification), or equivalent