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; • Coordination between arms, torso, and robot posture; • Control of approach, gripping, lifting, and placement of boxes; • Sequencing of the different actions of the task; • Real-time monitoring of execution
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methodologies for assessing the robustness and safety of fully human-operated, AI-assisted human-operated and autonomous systems, considering risk assessment aligned with the EU AI Act, reliability and robustness
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TRAINING: This work will start with a study on controlled data sharing methods in federated environments. Existing solutions will be tested for creating data spaces that align with the technical and
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the lifecycle of AI systems, from data preparation to model use, monitoring, and updating, should be aligned with human activities, organisational processes, and decision-making in industrial contexts
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and analyze relevant failure modes and degradation mechanisms, using methodologies such as FMEA and RCM, ensuring their alignment with decision-making problems in asset management.; - Develop models
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acquired across multiple anatomical regions to form a patient-level assessment. This PhD project will investigate novel deep learning methodologies that jointly model anatomical structure and prediction
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:; ; Improve and validate RADAR modules for detecting fruits and hidden structural elements in plants; ; Study optimized solutions with multiple RADAR modules, suitable for integration into manipulators and