597 structures "https:" "https:" "https:" "https:" "https:" positions in United Kingdom
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development for 1H and 129Xe lung MRI. Design testing and construction of RF circuits Fault finding and maintenance of existing RF coils Contribute to the supervision of PhD and undergraduate students in
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newer services use modern web architecture standards, are structured around APIs and are continuously built and tested using GitLab. They run on Docker containers and are deployed to a serverless
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(https://www.arcadiafund.org.uk ). The post holder will be employed on the Mapping Archaeological Heritage in South Asia (MAHSA) project and will join a team of researchers based in Cambridge. This project
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Arcadia (https://www.arcadiafund.org.uk ). The post holder will be employed on the Mapping Archaeological Heritage in South Asia (MAHSA) project and will join a team of researchers based in Cambridge
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language, particularly Greek or a Balkan language. You will bring experience of structured data entry in an online environment, alongside a calm, methodical approach and excellent attention to detail. You
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activities and contributing to scholarly publications and funding proposals. The position also offers structured mentoring and explicit support for career development, including opportunities to lead complex
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Experience with structure characterisation using microscopy and diffraction methods Desirable Application/interview Ability to work independently Essential Application/interview Evidence of presentation skill
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to work with Florian Hollfelder at the Biochemistry Department of Cambridge University (https://hollfelder.bioc.cam.ac.uk/ ). The project is part of the Horizon Europe Eu Marie Curie Network MetaExplore
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of Warwick. With world-leading expertise and facilities in electrochemistry, materials chemistry, spectroscopy, microscopy, modelling and battery and fuel cell construction and testing, we aim to develop next
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and materials engineering. They will do this by integrating modern data-centric approaches, such as physics-informed machine learning, structure-aware modelling, and digital-twin methodologies, with