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Field
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; Socioeconomic and demographic data; Hospital admissions and mortality records; Develop physics-guided and graph-based models for high-resolution environmental exposure estimation; Build explainable AI pipelines
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, or simulation-based evaluation Background in optimization, resource allocation, scheduling, or graph-based network analysis Exposure to resilience, reliability engineering, or security analysis (including
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students through a Space of Computational Thinking Skills. ICER 2013 67-74. [5] Besta M. et al. (2024). Graph of Thoughts: Solving Elaborate Problems with LLMs. AAAI Conference on AI. [6] Bittencourt, Ig. et
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processing Graph signal processing Machine learning - supervised, unsupervised and reinforcement and tools such as TensorFlow, PyTorch, Keras and GreyCat Neuromorphic computing, spiking neural networks Deep
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., entanglement, fidelity/noise, quantum repeaters) Experience with network modelling, performance analysis, or simulation-based evaluation Background in optimization, resource allocation, scheduling, or graph
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admissions and mortality records; Develop physics-guided and graph-based models for high-resolution environmental exposure estimation; Build explainable AI pipelines to identify which exposures matter most
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better suited systems (polystores or multistores [2,3]) by combining different data management paradigms (relational, document-oriented noSQL, graphs databases, columns stores, etc.). Moreover, to favor
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, tasks have a continuous evolution, and the precedence graph becomes dynamic. There is an initial method proposed in the literature, where a static model is proposed, introducing two states of products
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from reactive to proactive. The goal is to increase transparency and trust in the DNS namespace. Key research activities will include applying machine learning and graph-based techniques to uncover
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-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation methods for data assimilation; and graph-based multi