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Image Analysis Group (DIAG) at Radboudumc. We develop, validate and deploy novel medical image analysis methods, usually based on the newest advances in machine learning with a focus on computer-aided
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intelligence (AI) and machine learning(ML). Duties This position combines knowledge of the Earth observation (EO) domain (EO instruments, EO data, EO algorithms, modelling, etc.) and AI/ML, as well as data
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, simulations, and games, which use a variety of AI technologies to learn from, collaborate with, support, or improve humans; Deep Learning for Perception: Use of deep learning algorithms for computer vision
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(DSO) to resolve local congestion issues. The design of such an edge decision-making platform requires an understanding of distribution systems operation as well as machine learning and optimization
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boundaries of system-level modelling, analysis, design, exploration and synthesis beyond the current state-of-the-art? Or are you curious to learn more about the application of AI for system diagnostics and
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methods, integrating qualitative approaches (e.g., interviews, walk-alongs, focus groups) with quantitative techniques (e.g., computer vision, physiological sensing, environmental monitoring, crowd
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with world-changing potential. Our mission: to develop scalable prototypes of a quantum computer and an inherently safe quantum internet, based on the fundamental laws of quantum mechanics. To achieve
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mathematical control theory, and a keen interest in machine learning to apply for the PhD position within the Dynamics and Control section at the Department of Mechanical Engineering, Eindhoven University
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shifts in cell state and cell fate. Integrate spatial transcriptomics data to anchor these predictions in tissue context. Develop machine learning methods (e.g. graph neural networks, variational
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the SCM section will fill a maximum of one PhD positions this year that can be on any of these topics. Machine learning for stochastic last-mile deliveries In recent years, stochasticity has received