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fundamental AI methods together with their software implementations for interpretable statistical fault prediction and lifetime assessment in the context of Structural Health Monitoring of operating wind
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-loss events undermine statistical confidence. The aim is to develop i) edge intelligence (on-turbine smart algorithms for data preprocessing), ii) resilient data movement (error-tolerant, cybersecure
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characteristics. The insight will be used to assess global deep sea carbon turnover in the past and presently. Experience in lipid biomarker analysis, microbial cultivation, statistical modelling or machine
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complete, a master’s degree in computer science, mathematics, statistics, IT, engineering, biotechnology, bioinformatics, economics, or a related field. Experience with programming in Linux environments
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research in a wide range of mathematical disciplines and has three study programmes: mathematics (including a specialization in statistics at the master level), mathematical economics, and mathematics
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Denmark. The work consists of quantitative research, including developing research questions, conducting theory-driven statistical analyses of longitudinal register data, and, where relevant, linking
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of skills, and have the opportunity to explore interests in polymer synthesis, assay development, immunology, and statistics. Specifically, the work will involve: Organic synthesis Assaying polymers
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advance next-generation hearing assistive technologies through machine learning and statistical signal processing. The research in the centre focuses on enabling robust, real-time speech understanding in
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this study) and the novel models and data established in this project. Application of statistical methods to deal with the uncertainty and the probabilistic nature of the models. This study requires strong pre
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, Denmark, aims to advance next-generation hearing assistive technologies through machine learning and statistical signal processing. The research in the centre focuses on enabling robust, real-time speech