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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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, or erroneous data, Data cleaning and generation, Development of enhanced loss functions and information-theoretic methods for optimized data analysis, Machine learning-based image segmentation of tomographic
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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, contribute to a better world. We look forward to receiving your application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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combines: Fluid dynamics and heat transfer (theory and experiments), Computational modeling, and Machine learning / computer vision for data analysis and pattern recognition. The goal is to improve
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and small, contribute to a better world. We look forward to receiving your application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with
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research in collaboration with stakeholders. The PhD project is part of two key initiatives: the Competitive Timber Structures research profile and the BioGlue Center: Competence Centre for Bio-based
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Are you curious about how AI can transform learning in public environments? This is an opportunity to explore conversational AI and visualization in an interdisciplinary project with strong research
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corresponding knowledge in another way. Experience in one or more of the following areas is considered meritorious, Self-supervised learning, image denoising, or inverse problems, Transformer-based architectures