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analyses. Work iteratively with experimental colleagues to guide measurement design, interpret results and perform model validation. Contribute to reproducible modelling workflows (version control
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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respond to sound in ways that influence physiology, root function and pollination. This project will combine experiments, analysis and multiphysics modelling to establish credible mechanisms, limits and
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modelling tools to real-world challenges in antibody engineering. The position offers the opportunity to contribute to the development of new technologies for precise control of antibody glycosylation, with
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-ground processes and pollination. The research combines controlled experiments, advanced measurement and multiphysics modelling, and will generate open datasets and workflows to catalyse the emerging field
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may play in stress responses, below-ground processes and pollination. The research combines controlled experiments, advanced measurement and multiphysics modelling, and will generate open datasets and
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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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immunology with bespoke in vivo models to define and exploit therapeutically relevant subsets. The Research Fellow will lead studies on cytotoxic T cell mechanisms, oversee preclinical validation, and advance
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will be part of the ‘Accurate projections of climate recovery from a combination of historical data, simple models and AI’ Future Leaders Fellowship project, which seeks to understand how climate will
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. The successful candidate will contribute to an interdisciplinary research programme developing computational models to understand molecular interactions relevant to antimicrobial systems, biomolecular interfaces