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of surface-atmosphere interactions and limitations in current observational methods . Traditional remote sensing techniques are generally indirect, inferring evaporation from thermal imagery and reflectance
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mining has allowed us to obtain insights from large amounts of data for decades, and it is worth revisiting ideas and concepts from this field for the purpose of interpretable machine learning. Pattern
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on the expression but also the dynamic interaction of the key proteins for the endocannabinoid signalling and to target these systems in a cell-type specific manner to test whether their modulation might counteract
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tools for speech disorders, real-time language processing for human-robot interaction, and adaptive content generation in augmented and virtual reality environments. The project combines algorithm design
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aim to visualize the endocannabinoid system using advanced chemical tools focusing not only on the expression but also the dynamic interaction of the key proteins for the endocannabinoid signalling and
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part of a PED is developing sustainable heating and cooling solutions for neighborhoods. The goal of this project is to create a toolbox to help design local heating and cooling systems that fit local
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revisiting ideas and concepts from this field for the purpose of interpretable machine learning. Pattern-based modelling, for example, cannot only be used for exploratory data mining but also for predictive
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revisiting ideas and concepts from this field for the purpose of interpretable machine learning. Pattern-based modelling, for example, cannot only be used for exploratory data mining but also for predictive
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pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in
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part of a PED is developing sustainable heating and cooling solutions for neighborhoods. The goal of this project is to create a toolbox to help design local heating and cooling systems that fit local