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- UNIVERSITY OF VIENNA
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At the University of Vienna more than 10,000 personalities work together towards answering the big questions of the future. Around 7,500 of them do research and teaching, around 2,900 work in
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. The successful applicant will gain expertise in analysing large geological datasets, integrating multidisciplinary information and evaluating geological storage systems at regional scale. The outcomes will
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holder will be located in Central Cambridge, Cambridgeshire, UK. The role involves: Designing and carrying out quantitative single-cell infection experiments, Analysing large microscopy datasets Developing
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promotion and athletic performance, essential for maintaining functional capacity and driving physical development. However, prescribing RT is complex due to large inter- and intra-individual variability in
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About the project: Extreme Weather Storylines via Generative AI Supervisor: Dr Tobias Grafke, University of Warwick Generative machine learning techniques, as known for example from large language
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of large numbers of atoms, coarse-graining approaches seek to reduce of the number of degrees of freedom in a material model, thereby reducing computational costs and the environmental impact while
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are encouraged to apply, particularly where they have experience translating large-scale genomic data into biological insight. For informal enquiries regarding the role, contact Dr Emil Gustavsson at eg713
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for the creation of cellular machines. These synthetic designer de novo chromosomes allow us to address fundamental biological questions, systematically re-engineer genetic components, incorporate large-scale
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Sentinel-1, enable rapid large-scale flood detection but face challenges in generalisation, dependence on labelled data, and representation of hydrological processes. Existing UK operational systems combine
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a range of structural and spectroscopic studies, with a view to better understanding how this gene cluster can support large electrical currents. The student will join an active lab with considerable