28 developer-"https:" "https:" "https:" "UCL" positions at BIOMEDICAL SCIENCES RESEARCH CENTRE "ALEXANDER FLEMING" in United Kingdom
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https://www.ucl.ac.uk/work-at-ucl/rewards-and-benefits to find out more. Our commitment to Equality, Diversity and Inclusion We particularly encourage applications from candidates who are likely to be
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; and to enhance the development of area studies at UCL and among the wider academic community. We offer undergraduate, postgraduate taught and postgraduate research programmes, both in our four core
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Developing Novel Tools for the Analysis of Local Order using Total Scattering Data (TScat) EPSRC CDT in Developing National Capability for Materials 4.0, with the Henry Royce Institute PhD Research
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developing reliable behavioural markers of uncertainty during decision-making training, which can then be used to enhance trainees’ metacognitive awareness of peak uncertainty to benefit downstream outcomes
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About us University College London (UCL) is London’s leading multi-disciplinary university. UCL’s research and teaching is organised within 11 faculties, each housing a number of departments
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to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust, interpretable models from experimental and operational data
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with the CDT’s aim to achieve a sustainable wind farm lifecycle by developing methods for high-value reuse of composite turbine blades. Machine learning and non-destructive evaluation techniques will be
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/organic and the geopolymer matrix, in both the fresh cement paste and the hardened wasteform. This will allow us to develop next-generation low-carbon cement wasteforms for safe disposal of radioactive
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experts who combine technical excellence with a deep understanding of sustainable development in shaping societies. Our research focuses on sustainable built environment, mechanics and materials
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust