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tools, such as physics-informed climate and weather predictive models, and trustworthy datasets for training and analysis. Its work aims to improve prediction capabilities and understanding of climate
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human interaction, learning, and emotional engagement through multisensory integration and scene understanding. Predictive and Adaptive Systems: leverage multimodal data to predict human intent, improve
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interaction, learning, and emotional engagement through multisensory integration and scene understanding. Predictive and Adaptive Systems: leverage multimodal data to predict human intent, improve action
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W3 Endowed Professorship for “Hemodynamic Modeling in Atherosclerosis- (f/m/d) KSB Foundation W3 end
clinical application. The focus is particularly on photon-counting computed tomography (PCCT), 4D MRI flow imaging, and AI-supported analysis and modeling methods (e.g., CT-FFR, predictive software models
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robust descriptors (e.g., water activity, sorption, glass transition temperature, plasticization, porosity, internal distribution) and provide predictive guidelines to rationally select and design drying
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light–matter interaction through appropriate transport models, properly accounting for attenuation effects due to the materials. The activities will be carried out within the EIC PATHFINDER PREDICT
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to study chromatin and gene regulation in mammalian cells and human disease systems. Current ongoing projects include: statistical modeling and advanced machine learning/AI method development for predicting
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, regulatory, or multimodal biological data. Support target and mechanism prioritization by integrating model predictions with biological knowledge and external data sources. Work closely with academic partner
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on the project can be found here: https://hecustom.eu/ This post will contribute to the creation and validation of a digital twin (with biological bone models) to assess and interrogate the issue of
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, regulatory, or multimodal biological data. Support target and mechanism prioritization by integrating model predictions with biological knowledge and external data sources. Work closely with academic partner