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phenomena. The project will contribute to numerical method development as well as new understanding of flow physics and will make use of high performance computing (HPC) and advanced computational fluid
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lead and perform research in these areas, who will have practical experience of blast experimentation, underwater blast loading, and demonstrable computational modelling experience in a relevant area
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materials as an addressing these challenges. A large experimental research programme is now attempting to explore these materials further and develop them for use in devices. To underpin this research we need
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legal requirements. Commit to the training programme to develop the skills in a range of scientific techniques and the correct operation of basic laboratory equipment to successfully assist others in
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for training followed by validation and testing on unseen datasets including local cases. Correlation of the computational features with other clinicopathological variables, behaviour and survival will also be
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Overview This post is funded by the Quantum Computing Hub (QCI3) supported by the Engineering and Physical Sciences Research Council (EPSRC). The QCi3 Hub is part of Phase III of the UK’s Quantum
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Improving Deep Reinforcement Learning through Interactive Human Feedback
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computer program that will compute the cohomology of arithmetic groups for GL(2) over a definite rational quaternion algebras together with Hecke action. The second objective is to use this program to carry out
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confidentiality. Why does this matter now? Wearable devices have made round-the-clock health data commonplace, cloud computing places vast processing power at our fingertips, and patients are demanding care
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of agricultural weeds to herbicdes from an eco-evolutionary perspective. This project will develop models for the evolution of herbicide resistance that combines field data and computer models. The aim is to