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for Selective Absorbers. Your primary role will be to undertake theoretical and computational research on hyperuniform disordered photonic materials for frequency-selective solar-thermal absorbers based on metal
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The Opportunity: The Centre for Medical Informatics at the Usher Institute within The University of Edinburgh is looking for a non-clinical Post-doctoral Research Fellow to conduct original research
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programme grant “Total Body Nuclear Imaging for the Development of Nanotheranostics”. This Programme involves 15 co-investigators in a range of disciplines related to PET imaging strategies
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will involve the creation of an internationally leading research program. The role will be based full time at UCL but will involve extensive interactions with scientists at other SGC sites, in
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this information-gathering process. The successful applicant will have strong expertise in programming, and in particular developing AI-based computer vision methods. Ideally, they will have experience
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& International Health is seeking to appoint a Research Fellow in Health Data Science (with a focus on machine learning) to NeoShield , a multi-country implementation research programme focused on neonatal sepsis
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to support you in the development of your independent research and innovation career. As part of the programme we will offer you flexible support, including induction, mentoring and career development planning
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Researcher (R3) Application Deadline 11 Apr 2026 - 00:00 (UTC) Country United Kingdom Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a
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& International Health is seeking to appoint a Research Fellow in Health Data Science (with a focus on machine learning) to NeoShield , a multi-country implementation research programme focused on neonatal sepsis
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of the Korean Wave (Hallyu), commencing on 1 October 2026 or as soon as possible thereafter. This Fellowship forms part of the Hallyu South Korean Studies Programme and offers an exciting opportunity for an early