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acceptance? 2. Steel User Business models: How do DPPs afford new value-creating business models in steel using organizations such that a socially legitimate configuration of private/firm and public
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sophisticated condition assessment and decision-making capabilities. This PhD project tackles a critical challenge: how to develop robust machine learning models that can accurately predict component health and
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data, the consortium aims to develop a robust model that can better predict transplantation outcomes. This innovative approach will contribute to more reliable donor kidney selection, reduced rejection
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appendages using the (halo)archaea as a model. Studying the infection mechanisms of archaeal viruses can provide insight into the evolutionary history of viruses and help to understand adaptation to extreme
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learning models keep getting better, but how they make their decisions often remains unclear, because these depend on many incomprehensible model parameters that have been learned from data. For instance
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to distributed energy resources, enabling energy sharing, reducing grid congestion, and enhancing sustainability. The PhD project will focus on the governance models adopted for energy hub platforms. These include
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maintain robustness through evolution using live-cell imaging and multiscale modelling. Job description Cells are often described as intricate machines where proteins work together in a tightly coordinated
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a given discrete-event model that is safe with respect to certain requirements. Yet, the application of the approach is limited by the fact that tools for synthesis cannot always deal with the state
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mapping, with molecular approaches using human and animal disease models. Where to apply Website https://www.academictransfer.com/en/jobs/355039/phd-in-cardiac-electrophysiolog… Requirements Specific
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dialogue modelling), the series of experiments will result in four journal papers, to be integrated into a dissertation. You will participate in relevant conferences, workshops and seminars, and communicate