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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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qualification in ecology, marine biology, data science, environmental sciences, or related fields. Candidates with interdisciplinary backgrounds and strong quantitative skills are particularly encouraged
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One fully funded, full-time PhD position to work with Alessandro Suglia in the Embodied, Situated, and Grounded Intelligence (ESGI) group at the School of Informatics, University of Edinburgh
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critical mass on distributed radar, which is currently supported by prestigious and large initiatives including QuSIT and a newly awarded Royal Academy of Engineering (RAEng) Research Chair on distributed
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data sources to answer important population-level questions that will inform health technology assessment, policy, and practice. The successful PhD student will be embedded within an interdisciplinary
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require an IELTS score of 6.5 overall with a minimum of 5.5 in all sub-skills. International applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining
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Primary supervisor - Dr Myriam Charpentier Are you passionate about plant biology, endosymbiosis, system biology or bioengineering? Join a cutting-edge research project exploring how plants
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within the Vienna Doctoral School in Chemistry (DoSChem) – Austria’s largest doctoral training program in chemistry. DoSChem brings together more than 200 doctoral students and over 50 PIs, fostering
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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