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Large vision–language models (LVLMs) can describe driving scenes and support decisions [Li25], but they sometimes hallucinate objects, relations, or events that are not present [Liu24,Liu25]. In a
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, vital signs monitoring, joint radar and communications, sparse arrays, interference modeling, 4D imaging radars, distributed sensing, and tracking. SPARC has also collaborated with long-term industry
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this context, the role of subjective and objective measures, and their integration, is crucial for creating robust and interpretable AI models. Today, the complexity of multi-dimensional data and the need
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they sometimes hallucinate objects, relations, or events that are not present [Liu24,Liu25]. In a safety-critical domain, reducing hallucinations and improving robustness and trustworthiness are essential
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, materials characterization and device testing. Extensive experience with clean room processes and testing of resonators is required. •Enjoy working in an international team. Solid track of communication
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evaluation platform that tracks and ranks state-of-the-art LLMs for vulnerability detection, conducting rigorous testing to ensure accurate assessment of model robustness against adversarial attacks. Is Your
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, DRX, XPS, etc.). Experience in Atomic Layer Deposition, mechanical, electrical and/or thermal characterizations of materials, is a plus. High-level scientific and technological track record related
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of materials, is a plus. High-level scientific and technological track record related to material chemistry and/or electroplating is a plus. Strong communication and interpersonal skills; The candidate should be
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associated threats. The research project of the PhD student will thus focus on defining methods to track, monitor, and manage the use of GenAI. While this can rely on recentely proposed telemetry framework
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modeling, 4D imaging radars, distributed sensing, and tracking. SPARC has also collaborated with long-term industry partners such as IEE S.A (www.iee.lu ), University of Naples Federico II, US Air Force