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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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workshops as a means to continuously improve technical and theoretical knowledge. Ability to obtain information from literature and from colleagues and integrate this into developing and optimizing work
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based at the Department of Obstetrics and Gynaecology, University of Cambridge. They investigate the mechanisms by which sub-optimal nutrition in early life can affect reproductive ageing, the impact of
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and waste by improving the supply chain through innovative, sustainable solutions. About the Role The successful candidate will collaborate with Westfalia Fruit and Cranfield University to optimize
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subsystems, components (e.g., protocol implementation, etc) Excellent theoretical and computing kills in the areas of network optimisation (Game Theory, ILP, NP problem relaxation, Lagrange optimization
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drive the gradual development of these technologies toward real-world applications. This involves engineering experimental hardware for cell culturing workflows, optimizing experimental processes, and
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, mutualisms among invading organisms in forests, risks and benefits of non-native trees in forestry, social perceptions of non-native species in forests, economic optimization of forest biosecurity, and the