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volatility. CLASSIQUE is organized into four Research Thrusts that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and
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competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT4 on Reliability and Trustworthiness
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that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT3
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interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT3 on representation
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well as developing solution algorithms applying mathematical and computational approaches. The group has a particular focus on automated decision making in autonomous cyber-physical systems. Autonomous systems and
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above, focusing on generative and Bayesian models relying on methods ranging from mathematics, algorithmic design, to implementation, and experimentation. Analyzing large-scale environmental datasets
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development and generative AI tools is an advantage as is an interest in sustainable and ethical AI. You should be committed to producing research that not only advances theory but also benefits Danish society
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scientists and researchers across five Danish universities building training and research infrastructure. Your competencies We expect you to have a master’s degree in statistics, computer science, mathematics
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focus on factory and line level, where three research topics are defined: 1) Conceptual design principles and methods for resilient manufacturing systems. This topic will build upon existing theory
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for resilient manufacturing systems. This topic will build upon existing theory on modular and reconfigurable manufacturing systems and develop methods and model-based approaches to design and evaluate resilient