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reinforcement learning Enhancing transparency and contestability of decision-making processes, taking a multimodal approach to reveal the reasoning behind complex AI-driven planning and learning algorithms
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(LES) results. Key Responsibilities: Develop and refine numerical algorithms for real-time wind field forecasting. Validate forecasting models against high-fidelity LES data and field measurements
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of computer architecture and digital design; Basic understanding of MRI algorithms is a plus; The ability to work in a team and take initiatives. TU Delft (Delft University of Technology) Delft University
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-edge control algorithms for the security and resilience of cyber-physical systems? We welcome you to apply for a PhD position in the SecReSy4You Doctoral Network, a European Union-wide Doctoral Network
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theory? Do you want to develop cutting-edge control algorithms for the security and resilience of cyber-physical systems? We welcome you to apply for a PhD position in the SecReSy4You Doctoral Network, a
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, to create a unified and reliable representation of structural integrity. The work expands on TU/e’s contributions by developing algorithmic components for detection and classification of defects and anomalies
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types. Your algorithms will first be evaluated through simulation using real operational datasets, and later deployed and tested at two physical facilities: a kW scale testbed at TU Delft’s Green Village
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fidelity, enabling precise characterization of transmitter errors and nonlinearities. These measurements will be used to generate error signals for advanced AI-assisted digital predistortion algorithms
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, evaluate and describe novel algorithms for learning concepts with theoretical guarantees from unstructured data; present research results at international conferences, workshops, and journals; pursue and
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HAPP: harmonised appraisal tool for grading and individualised feedback that is integrated into the learning management system (LMS) http://happ.rsm.nl/ Opens external Thesis coach finder: application