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, including deep learning architectures, self-supervised and unsupervised approaches, physics-informed neural networks, transformer-based models, and/or quantum-inspired learning techniques, capable
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range of downstream tasks. Candidates will be requested to develop novel methodologies within the artificial intelligence framework for effectively and efficiently process image time series for semantic
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required staff training, process redesign and collaboration among diverse experts to adapt systems and practices. Consequently, new tools and methods were developed to support organisations (Bhalavat et al
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different tasks and physical platforms, ensuring consistent performance in unseen real-world scenarios. Where to apply Website https://phd.fbk.eu/calls/detail/generalization-in-vision-language-action-models
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hampered by high data collection costs and poor out-of-the-box transferability. This doctoral project aims to bridge the gap between Generative AI and Physical Embodiment. The goal is to investigate closed
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at the far edge of the computing infrastructure. Given the challenges of limited computation, energy constraints, and communication bottlenecks, there is a growing need to process data locally while ensuring
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remains a challenge in practice, due to factors such as poor scalability, lack of automation, the interplay between computation and physical aspects, or the increasing complexity of the software and its
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within a Research Infrastructure? No Offer Description The design process of complex systems must guarantee not only the functional correctness of the implemented system, but also its safety, dependability
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within a Research Infrastructure? No Offer Description This PhD project integrates advanced materials modelling and theoretical nuclear physics to support next-generation nuclear energy systems, with a
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of such techniques, providing results that will be exploited in the analysis of experimental data and in view of applications in astrophysical contexts and in the search of physics beyond the Standard Model. Where