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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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collaboration between the Universities of Exeter and Newcastle. Exeter has internationally recognised expertise in multi-omics, state-of-the-art sequencing, and computational pipelines. The Exeter team has led
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Project details: Supervisors Dr Andy Cunliffe , Oppenheimer Associate Professor of Geospatial Ecology, University of Exeter Professor Ted Feldpausch , Professor of Terrestrial Ecology and Global
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), machine learning (ML), deep learning (DL) and Data science methods for medical image analysis, to autonomously grade the fundus images from large datasets. This will be supported by Professor Neil Vaughan
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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computational fluid dynamics and numerical modelling will be used to simulate performance under varying runoff scenarios, pollution loads and climate conditions. By developing advanced road gully designs with