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Vacancies PhD position on Liveness from causality analysis Key takeaways Programs often suffer from liveness issues - they may get stuck or fail to make progress. How can we address this? Our
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providers, recursively forming complex supply chains that are difficult to analyze. As a result, operators may unknowingly introduce technical, operational, and regulatory risks – especially in critical
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will focus on the development and application of innovative methods for data-analysis and integration, including AI based methods to combine the different types of data, using data from different case
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analysis, and high-performance simulations? We offer a challenging PhD position in the Mathematics of Computational Science group to design and analyse novel structure-preserving methods for stochastic
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expertise in healthcare, technology, and quantitative analysis. Using data from the TopTreat consortium, you will identify prognostic markers to support personalized treatment, and assess their health
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structures. Other aspects of the research include a numerical framework for the sensitivity analysis to facilitate design optimization and experimental system identification. Information and application
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becomes a real challenge to uniquely extract information on their layer properties in order to understand and improve their performance. A way to “break the nanometric barrier” for structure analysis is to
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these impacts. Next, you will develop a method to include water quality in a water supply and demand balance for cities. This method development should ground in a document analysis and might be supported by