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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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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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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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-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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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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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
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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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networks within the various Research Centres/Branches/IRAP of NRC. He/she/they will assist in managing and maintaining the Mac computers in the production environment using centrally managed tools like Jamf
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reliability and operational efficiency. Determining the optimal size and location of PSTs within a network is inherently complex due to the nonlinear and dynamic nature of power systems, necessitating the use
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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