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expertise in deep learning and representation learning applied to biological data, experience with large-scale multi-omics datasets (such as single-cell and proteomics), and strong programming skills in
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strong numerical background with proficient programming skills and a proven research record through publications and code development. Experience in developing discrete element models (DEM) or hybrid
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to contribute to the ‘Biological Nitrogen Fixation’ program. This initiative seeks to engineer biological nitrogen fixation into widely grown crop plants to improve yields and reduce global reliance on synthetic
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to the ‘Biological Nitrogen Fixation’ program. This initiative seeks to engineer biological nitrogen fixation into widely grown crop plants to improve yields and reduce global reliance on synthetic fertilisers
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modelling, turbulence modelling, and computational fluid dynamics. Experience in chemical kinetics modelling, multiscale simulation methods, and scientific programming is essential. Experience with plasma
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experiment will be an advantage. Candidates are expected to demonstrate the ability to communicate effectively, plan and execute research activities, and work in a team. Please direct enquiries about the role
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We are seeking a highly motivated and talented post-doctoral researcher to join our research programme in metasurfaces. The position is funded by the three-year Leverhulme Trust Research Project
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resources effectively Understanding of and ability to contribute to broader management/administration processes Contribute to the planning and organising of the research programme and/or specific research
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Systems Engineering), along with excellent computing and programming skills in multiple languages and environments. You will also need a problem-solving ability to manage and analyse manufacturing datasets
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The post is within the Thanzi La Mawa programme. The primary objective of this team is to improve population health and reduce health inequalities by helping to enhance the efficiency and equity