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that the electrolysers operate safely and reliably while fulfilling the intended specifications. The knowledge gained from the experiments will be used to determine the appropriate risk and reliability analysis
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established methods of microstructural analysis and mechanical testing with new schemes such as Acoustic Emission for non-destructive assessment of degradation and Machine Learning for development of predictive
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Vacancies PhD Candidate in Explainable AI for Earth Observation Key takeaways With the growing integration of Artificial Intelligence (AI) in geospatial decision-making processes, ensuring
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Decision Intelligence for Supply Chain and Operations Optimization. The successful candidate will contribute to cutting-edge research at the intersection of Statistical Machine Learning and Generative
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subprojects (SP): 1) SP1 includes desk research and case file analysis about how decisions are based on what kind of legitimations 2) SP2 unfolds how decisions are justified in-the-making via shadowing and
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research and case file analysis about how decisions are based on what kind of legitimations 2) SP2 unfolds how decisions are justified in-the-making via shadowing and narrative interviews 3) SP3 focusses
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relationships. You are motivated to acquire new skills and work in a multidisciplinary team. You have practical experience with experimental work and data analysis. You act with attention to quality, integrity
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for health policy decision-making, these methods will be developed using a Bayesian framework. This PhD project will deliver a substantial contribution to original research in the area of health data science
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Centrum Wiskunde & Informatica (CWI) has a vacancy for a 4-year PhD position (m/f/x) on the subject of Reliable AI-powered Data Analysis in collaboration with the University of Amsterdam. Interested
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. The system will leverage cutting-edge techniques in Natural Language Processing (NLP), Machine Learning (ML), and Multimodal Analysis to conduct adaptive interviews, assess candidate responses, and generate