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and decision support for railway operations and maintenance. The successful candidate will work on developing, testing, modelling, and validating methods for DAS-based monitoring of railway
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comprehensive validation framework will be established, beginning with offline simulations using detailed distribution network models to test and benchmark the proposed control strategies. These developments will
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packages, where data, technologies and biological models will be shared across projects through joint supervision, network activities and academic and industrial secondments. The position is allocated
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between multiscale flows involving ocean surface waves, submesoscale current, turbulence, and wind actions. The research aims to derive a highly accurate and efficient theoretical models by extending newly
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requirements at the energy edge. Further, you will incorporate compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand
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(Italy) and IRD (France). The topic is the measurement of waves, and the turbulent mixing and entrainment of air bubbles and oil droplets, with the aim of improving existing modelling tools for marine oil
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This PhD project focuses on developing formal methods and knowledge representation techniques for the modelling and analysis of complex manufacturing and intralogistics systems, such as highly automated
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intervention studies to determine the most effective ways for healthcare professionals to collaborate in the best interest of the patient, and we delve into health economics to establish models for cost savings
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of national and international funding agencies, as well as from industry. Job description We are seeking an ambitious candidate to develop Machine Learning models and frameworks for time series
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of waves, and the turbulent mixing and entrainment of air bubbles and oil droplets, with the aim of improving existing modelling tools for marine oil spills. The Post.Doc. will be a key person in the project