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numerical models and machine learning tools to predict loads, assess structural responses, and identify damage under extreme conditions. By combining computational simulations with data-driven approaches
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Computer Science (or close field) with strong foundations in data management, machine learning, and software engineering. Coursework or projects in NLP/LLMs, information retrieval, knowledge graphs/ontologies, data
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the researchers from Department of Automation and Process Engineering will play a key role. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early
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the following conditions: OBJECTIVES | FUNCTIONS The purpose is to continue the research on Machine Learning methods applied to optimization techniques, in particular for the veicule routing problem. The idea is
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Computer Science (or close field) with strong foundations in data management, machine learning, and software engineering. Coursework or projects in NLP/LLMs, information retrieval, knowledge graphs/ontologies, data
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resilience of bridges under climate change-induced hazards such as flooding, scour, and debris impacts. The research aims to develop advanced numerical models and machine learning tools to predict loads
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of Visual Intelligence is to develop novel, innovative solutions based on deep learning to extract knowledge from complex image data. Deep learning, aided by machine learning techniques in general, has led
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perform 3D single-particle tracking and establish pipelines to characterise the particle motion using a combination of established tracking algorithms and machine-learning-based approaches. Additionally
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combine intracranial electrophysiological recordings in humans with behavioral experiments and advanced analytical approaches, including machine learning and statistical modeling. It has two main objectives
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to: compositional multiphase reservoir simulation upscaling or screening methodologies optimization of well positions and control strategies economic assessments machine learning or proxy-model based methods field