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of analytical chemistry and machine learning. For more information please contact Prof. dr. Deirdre Cabooter, mail: deirdre.cabooter@kuleuven.be . Where to apply Website https://www.kuleuven.be/personeel/jobsite
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an analytical-computational framework for a “living” 4D Digital Twin (3D + time) to enable automated progress monitoring and multi-domain safety assessment in civil engineering applications. The project focuses
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people and the world in which they grow and learn. Current AI tools—often considered “black boxes”—are characterised by a critical idiographic–nomothetic discrepancy. They are trained on static, aggregated
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mechanisms for distributed learning, real-time analytics, and AI-driven decision-making across heterogeneous environments (edge-cloud), contributing to the realization of intelligent and self-optimizing 6G
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autonomous and efficient network/service management. The PhD candidate will investigate innovative mechanisms for distributed learning, real-time analytics, and AI-driven decision-making across heterogeneous
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open to candidates with a strong interest in either: i) Radio/physical-layer intelligence (e.g., channel estimation, CSI prediction, edge-deployable deep learning), or ii) Networking and control-plane
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translate into concrete health outcomes. The BRANCH project wants to change that. By combining conceptual work on green space typologies, advanced geospatial analytics, AI-based image analysis, citizen
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approach, combining machine-learning–enhanced text-as-data analysis with qualitative discourse analysis. The project aims to produce a set of high-quality scholarly outputs, including peer-reviewed journal
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) Radio/physical-layer intelligence (e.g., channel estimation, CSI prediction, edge-deployable deep learning), or ii) Networking and control-plane intelligence (e.g., reinforcement learning for scheduling
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children learn new words not only by listening to a storyteller but also by processing multimodal signals such as iconic gestures and gaze direction. Using eye-tracking in both real-life and digital contexts