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Applications are invited for a fully funded fixed-term position at the Research Associate (PostDoc) level in de-risking cirrus modification. Cirrus cloud modification (CCM) could in-theory mitigate
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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the theory by putting it on a lattice. The resulting equations are solved numerically using specialized Monte Carlo techniques. There are many applications that require the solution of QCD so that the standard
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This research aims to develop an innovative framework that integrates health-seeking behaviour—the actions individuals take when they perceive a health problem, grounded in behavioural theories
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, partial differential equations and scientific computing, to name a few. There are competing LC theories e.g., molecular-level models with molecular-level information, mean-field models that average
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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
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cryptography, and will have an interest in interdisciplinary research. Knowledge of mathematics, particularly number theory, to the equivalent of first-year undergraduate level is desirable. We strongly
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-based symbolic machine learning. The aim is to give the industrial widely used NewWave theory (a theory that predicts the linear shape of extreme waves) a modern twist to account for the important
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machine-learning surrogate models capable of delivering near-DFT (density functional theory) accuracy in just a few CPU seconds per structure. This approach will enable the high-throughput screening of tens
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There is a great deal of interest in the nature of QCD, the strong interaction force of particle physics. It has a fascinating personality - in all but the most exotic situations, it confines quarks