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. The work involves areas such as AI-assisted automation engineering, digital twins, semantic modeling, secure data exchange, and reconfigurable production architectures. The research is carried out in
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Observation, and Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal processing
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for linking task planning and ontology-based knowledge representation within the framework of the Humfleet project. His role will be to set up a semantic and automated representation of a fleet of heterogeneous
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experiments to investigate the diverse mechanisms (e.g attention, acoustic and semantic processing) involved when humans listen to naturalistic auditory scenes. The experiments will collect behavioral, MEG (OPM
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generated images and videos (Deepfakes) are increasingly realistic from a vi- sual point of view. Their use to manipulate information is obvious. Several methodologies for generating semantic content exist
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Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal processing, network resource
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adaptable object handling in complex real-world scenarios, including those involving deformable objects and uncertain conditions.. Semantic Navigation & Mapping – Designing solutions for robot navigation
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cryptographic methods, and semantic communication, supported by machine learning and AI techniques. Key Responsibilities: Conduct cutting-edge research in: Quantum key distribution (QKD) and quantum-safe
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focuses on developing next-generation secure communication frameworks that integrate quantum key distribution (QKD), advanced cryptographic methods, and semantic communication, supported by machine learning
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is to determine how memory mechanisms can be generalised across linguistic domains, from the lexicon through syntax to discourse semantics, and how plausible memory models can predict diverse