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Field
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distresses and causality. The ultimate goal of such a knowledge representation is to create a future-proof framework that enables FAIR data sharing within initiatives such as Knowledge-Based Pavement
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requires systematic data handling to establish a clear link between distresses and causality. The ultimate goal of such a knowledge representation is to create a future-proof framework that enables FAIR data
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queries within embedded knowledge graphs. It will involve designing or adapting efficient indexing structures tailored for vector databases and exploring hybrid neurosymbolic techniques to enhance query
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Description The research group of Systems Neuroscience of IMBB under the European Program ERC-2022-STG - NEURACT entitled “Untangling population representations of objects. A closed loop approach to link neural
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counterfactual reasoning frameworks that uncover latent mechanisms and enable principled hypothesis testing. Our goal is to advance the theory of representation learning and causal inference in high-dimensional
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evaluate feature engineering and data representation strategies for heterogeneous datasets obtained from material synthesis, characterization, and functional testing. Apply uncertainty-aware modeling, active
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representations from massive amounts of raw data, typically using large-scale models that incorporate only minimal prior domain knowledge. Such representations can support a wide range of downstream tasks. However
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illness at the national level. Through a combination of extant personal oral stories and archival sources, together with new digital humanities representations of data about infection and vaccination rates
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to support policymakers in designing effective climate strategies. In this PhD project, you will work on improving the representation of feedbacks, tipping points, and extreme events in the MIMOSA model, a
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or research centers in the field of transport and energy, contributes significantly to the advancement of knowledge on these critical issues, both for the climate and the environment. To respond