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robust feedback control theory for nonlinear dynamical systems using input-output operator theory and graph separation theory. Excellent knowledge of input-output dissipativity theory, input-output
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algorithmic graph theory. The purpose of the role is to contribute to the project "Algorithmic meta-classifications for graph containment", working with Professor Matthew Johnson, Dr Barnaby Martin and
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The Role Applications are invited for a Postdoctoral Research Associate in Computer Science with a particular emphasis on structural and algorithmic graph theory. The purpose of the role is to
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of focus include random graphs and trees (combinatorial properties, scaling limits, coalescent and branching structures, random matrix theory), stochastic and Lévy processes in infinite-dimensional spaces
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mobile robotics, you will manage own academic research and administrative activities, adapt existing and develop new methodologies in robotics, design working algorithms from theories, deploy and test
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structural and algorithmic graph theory. The purpose of the role is to contribute to the project “Algorithmic meta-classifications for graph containment”, working with Professor Matthew Johnson, Dr Barnaby
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Ramsey Theory and Graph Packing. Another example of the interplay between algorithms and combinatorics arises in the context of graph packing. See the following paper: https://epubs.siam.org/doi/abs
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to develop a knowledge-aware and event-centric framework for natural language understanding, in which event graphs are built as reading progresses; event representations are learned with the incorporation
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generated from density functional theory simulations, we aim to interpret complex TERS images and push the limits of nanoscale optical imaging. The student will develop and implement new theoretical
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graph neural networks for complex sensor networks such as those involved in brain imaging Develop and test data-driven methods for image and video processing for microendoscopy. Key Duties and