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We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal
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A 3.5 year, fully funded full-time PhD studentship is available for commencement January 2027. This is a collaborative project between the Centre for Cultural and Media Policy Studies, University
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Can AI learn to reason like a human - and recognise when it isn’t sure? This PhD tackles that challenge in a high-impact setting: interpreting 3D digital models of rock formations built from drone
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with nuclear fuel modelling, machine learning
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and you may be eligible for an exception to this work arrangement. Alternative work arrangements may also be considered to accommodate candidates as required. To learn more about these options, please
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. Delivered in collaboration with Intel, including industrial co-supervision. The student will work with Durham University academic supervisors and an Intel co-supervisor on compact Physical AI, data-efficient
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/or QGIS) Very good English language skills, both written and spoken Basic knowledge of the German language or the willingness to acquire it for the purpose of knowledge transfer Openness, creativity
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PhD Scholarship in Development of Cement-Free Living Building Materials for Sustainable Construction
research environment at DTU Construct, collaborating closely with researchers at DTU Bioengineering and internationally with TU Delft, while benefiting from access to state-of-the-art facilities
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, military, and diplomatic repositories in the UK and internationally. The Centre's methodological approach is interdisciplinary, and the successful candidate will benefit from training and collaboration
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scientific initiative focused on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and