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skills and ability to work across disciplinary boundaries. Desirable: Experience with image-based modelling workflows (CT/XCT segmentation-to-mesh pipelines). Experience with inverse problems, uncertainty
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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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for Selective Absorbers. Your primary role will be to undertake theoretical and computational research on hyperuniform disordered photonic materials for frequency-selective solar-thermal absorbers based on metal
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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
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) at the University of Southampton. The successful candidate will contribute to an interdisciplinary research programme developing computational models to understand molecular interactions relevant to antimicrobial
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-of-the-art structural modelling and computational protein design approaches to understand and engineer enzymes that modify IgG Fc N-linked glycans. The successful candidate will use tools such as AlphaFold
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predictive modelling, classification approaches, pathway analysis, and topological data analysis. You will be based within the laboratory of Professor Paul Skipp, working closely with colleagues in the Glyco
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and translation. You will be based in the School of Electronics and Computer Science (ECS), working alongside an interdisciplinary team led by Dr. Shelly Vishwakarma (s.vishwakarma@soton.ac.uk ), in
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with an industry partner and the UK Space Agency. Key responsibilities include: Developing a second-stage plasma accelerator based on magnetohydrodynamic (MHD) principles. Optimising ICP (Inductively
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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