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regulatory obligations. Hydraulic simulators are physically detailed but computationally slow and calibration-intensive, limiting large-scale scenario exploration and optimisation. Purely data-driven
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across disciplines An independent, self-motivated approach to research You'll gain skills spanning dynamical systems theory, data science, earthquake science, and soil ecology, working with large, real
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About the Project As federated learning systems become increasingly embedded in high‑stakes domains where data cannot be directly shared, such as healthcare and finance, the ability to selectively
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data such as online customer reviews. This work will produce a generalisable, open-source tool for computing variable-threshold accessibility indices. Examine the relationships between N and health and
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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CD3 is a new, multidisciplinary and multi-institutional strategic national research programme dedicated to using data to transform our understanding of cancer risk and enable early interception
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adapted for the developing brain. To do so, we will use high-quality MRI data in a large cohort of infants (N~1000), including subgroups with clinical conditions. Our approach has the potential to deliver
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, and coalescence of smaller droplets, eventually generating droplets that are large enough to fall from the cloud under gravity. However, the turbulence within clouds is highly intermittent, due
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At the University of Vienna almost 11,000 personalities work together towards answering the big questions of the future. Around 7,700 of them do research and teaching, around 3,000 work in
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@leeds.ac.uk Dr Keeran Ward: K.R.Ward@leeds.ac.uk Project summary This proposal addresses the need for process solvents and basic aromatic feedstocks. Drug products, and their manufacture, involve large amounts