15 evolution "https:" "https:" "https:" "Multiple" "Newcastle University" PhD positions at Loughborough University
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Volcanic islands are exciting real-world climate and landscape laboratories. When geologically young (<10Ma) they provide a simplified and spatially limited setting for testing landscape evolution
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datasets with phylogenies and environmental variables, the project aims to rapidly explore trait evolution, predict dispersal potential, and assess climate-related risks. This work bridges biodiversity
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, sediment transport, and flood risk, delivering evidence to guide sustainable river management and climate resilience. Based at Loughborough University with collaboration from Newcastle University, you’ll be
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identification of deterioration processes and assessment of their evolution/extent. Please reach out to the primary supervisor, Prof. Craig Hancock , if you have any questions. Entry requirements: We are looking
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are available on the International website (http://www.lboro.ac.uk/international/applicants/english/ ). Funding information: The studentship is for 3 years and provides a tax-free stipend of £20,780 per annum (in
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selection criteria will be used by academic schools to help them make a decision on your application: https://www.lboro.ac.uk/study/postgraduate/apply/research-applications/studentship-assessment-criteria
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subject to final approval by the University. The following selection criteria will be used by academic schools to help them make a decision on your application: https://www.lboro.ac.uk/study/postgraduate
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ecosystem mapping, multiple case studies, and a firm-level survey to build a multi-level framework explaining why digitalisation unfolds unevenly across places and sectors. The project will pay particular
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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, the system will analyse data across multiple scales—from broad landscape views to microscopic symptom detection. Through vision–language AI models, the framework will interpret visual and textual data