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Field
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professional network spanning academia, industry, and national research centres. Through this multidisciplinary project, the student will develop expertise in: Contribute to the development and operation of
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workshops, career development, and networking Join a dynamic institute hosting over ten atmospheric chemistry research groups, offering rich opportunities for collaboration and learning Extensive
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effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable
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-enhanced exact methods, particularly focusing on Column Generation (and Branch-and-Price), to improve scalability and convergence in solving complex optimization problems. In collaboration with your
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Your Job: The main objective of this PhD project is to achieve a better understanding of the efficient propulsion of trypanosomes through complex crowded environments, mimicking biological tissues
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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The Child and adolescent Health Impacts of Learning Indoor environments under net zero (CHILI) Hub is a program funded by the MRC and NIHR, the goal of which is to understand the health effects we
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Overview: As data becomes more accessible, new challenges arise around how best to use it—especially in complex, multi-system environments like aerospace. Ontologies offer a powerful solution by
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can be varied. Crucially, the models we derive will be validated by real-world measurements to ensure our simulation environments are realistic and scalable to more complex radar networks. This will
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processing, signal processing, network resource management to improve the performance of the future wireless communication systems. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G