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will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Theodoros Kapourniotis, National
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professional expertise. Entry Requirements: A first-class or strong 2:1 degree in a relevant science or engineering subject such as Mechanical Engineering, Aerospace Engineering, Materials Science, Physics
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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other top UK institutions to develop world-class social science researchers. We’re proud to support the future leaders of social science in academia, public services and industry. SEDarc are offering
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of Human, Social and Political Science. BSPP has an ambitious growth plan including launching an M.Phil in Digital Policy alongside an expanded M.Phil in Public Policy, and the development of a new PhD
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-treatment facilities, and biorefineries. Feedstock choice, regional dynamics, and process side-streams all affect costs, energy use, and emissions. This PhD project will develop advanced computational models
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the successful candidate embarking on a PhD programme at LSHTM. It is anticipated that the role will lead to a further 18 month funded opportunity at Max Planck Institute for Demographic Research (MPIDR), in
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to realise their full potential, from academic achievement to mental and physical wellbeing. We are committed to progressing the diversity and inclusion agenda, for example; gender diversity in Science
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an important role in the efficient integration and management of solar energy in modern power systems. The studentship project aims to develop a novel PV forecasting model based on physics-informed neural
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respond during platelet formation and how diseases like long COVID may alter this process. The goal is to better understand the biology of platelet production and improve lab-based methods for generating