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the development of components using agent-based modeling techniques, reinforcement learning, and other explainable artificial intelligence modules for decision-making, situation assessment, and operational support
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established). Strong motivation for science, with a genuine interest in problem-solving, a commitment to contributing to society, and a willingness to continuously learn and develop new skills. What will you do
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of AI and machine learning techniques, including handwritten text recognition and probabilistic indexing, to improve access to historical sources. Ensuring the archive is sustainable, accessible, and
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learnINg for LArge scaLe InTerconnected sYstems) focused on "Fairness in flow allocation: an optimal transport approach". The FINALITY DN advances the theoretical computer science curriculum focusing
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characterize new reticular materials (COFs), and use them as precursor for the generation of new polymers via Clip-off chemistry. The candidate will acquire a great experience in supramolecular, reticular and
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characterization, and integration of machine learning to correlate synthesis conditions with functional performance. The goal is to establish predictive synthesis strategies for oxygen vacancy control, with