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identification and machine learning. The key challenge is striking a balance between, on the one hand, modelling the physical, dynamic and nonlinear behavior of the components with sufficient physical accuracy
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Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter identification and machine learning. The key challenge is striking a balance between, on
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computational model to capture the complex transport of gases, liquids, and charges in these porous structures, including the complex interfaces between them. Insights from the model will directly guide the
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theory, and machine learning. They will have access to a fully equipped lab and benefit from collaborations within the ERC team and across TU Delft. There will be opportunities to present at leading
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geospatial workflows on an abstract level, using purpose-driven concepts and conceptual transformations; develop AI and machine learning based technology to automate the description and modeling of data
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researchers in soft robotics, control theory, and machine learning. They will have access to a fully equipped lab and benefit from collaborations within the ERC team and across TU Delft. There will be
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, electrical engineering, technical medicine, or a related field. You have a solid background in biomedical signal analysis, physiology dynamic system, and machine learning technologies, and preferably have
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), photoplethysmogram (PPG), Electrodermal activity (EDA), and contactless movement and physiology signals. Specifically, the PhD researcher will develop physiological-model-based artificial intelligence technologies
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provide to infrastructure managers You will be part of a multidisciplinary project with leaders in the domain of infrastructure governance and modelling. You will learn to conduct research independently and
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infrastructure managers You will be part of a multidisciplinary project with leaders in the domain of infrastructure governance and modelling. You will learn to conduct research independently and grow