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analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and
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the use of synthetic data in precision medicine research and applications through development of AI algorithms, tools and other processes to allow for the enrichment of clinical data sets Providing training
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research work will be to devise efficient algorithms for source separation in DAS measurements. Issues such as large data volumes that can exceed 1 To per day and per fiber, instrument noise, complex nature
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typically around 200nm in the transverse plane and 400nm in the optical axis. Over the recent years, several super-resolution techniques have been developed to overcome this drawback. Among them we focus
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repeater based quantum internet. To this end, our overall goal is to develop quantum nanophotonic chips, in which colour centres are used for interference exepriments to mediate entanglement between distant
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instructor for Carpentry courses, Elixir Train-the-Trainer courses, or as a teacher in university-level education Laboratory experience in omics environments, such as sequencing, transcriptomics, or proteomics
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(UCA). He leads the eBRAIN research group and develops a interdisciplinary research activity on embedded Bio-inspiRed AI and Neuromorphic architectures, especially based on SNNs. LEAT is a mixt research
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provides methodological support in statistical planning as well as analysis & data handling for various laboratories and research groups. The methodology group explores or develops new methodologies to help
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within the Faculty. Along with the disciplinary approach a very ambitious interdisciplinary research culture has been developed. The faculty's research and teaching focuses on social, economic, political