482 developer-"https:"-"https:"-"https:"-"UCL" Fellowship positions in United Kingdom
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information/data from one structure can be used to manage similar structures from the same population. New machine learning, sensing and digital twin technologies will be developed with the aim of driving new
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–dielectric–metal resonator platforms. The project develops hyperuniform disordered metasurfaces, a novel class of photonic structures in which structural correlations are precisely controlled to achieve
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. Within a collaborative team, you will contribute both to cutting‑edge methodological development and to the creation of accessible, open‑source tools used by public health professionals and researchers
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to the development of research strategies Publish results of own research Supervise PhD students Contribute to the Department/School through management/leadership Develop and make substantial contributions
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London School of Hygiene & Tropical Medicine; | London, England | United Kingdom | about 1 month ago
. The goals are to develop a greater understanding of basic mechanisms of immunological protection versus pathology, and to apply this knowledge to the development of interventions and the identification
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, shaping quartz at high temperatures, programming furnaces and carrying out a suite of characterisation measurements on the final products of growth. Hands-on experiments & development of capabilities, and
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to concentrate on innovative metasurface-engineered tubular designs, advanced ceramic manufacturing, and high-temperature performance evaluation. The project involves developing a mini-scale tubular high
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to the creation of knowledge in the field of early cognitive and social-emotional development, by undertaking a specified range of activities within an established research programme and/or specific research
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technology sensors Liaise with others within QuSIT to develop trials which answer scientifically interesting research questions and/or demonstrate the benefits of the QT gravity gradiometer in a range of
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This post will advance the application of Machine Learning (ML) in weather forecasting and hydrological prediction. The Research Fellow will develop ML methods for postprocessing numerical ensemble weather