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a generative AI model capable of predicting bird plumage based on images of their habitats. - Test the hypothesis that color patterns generated from images of a new habitat more closely resemble those
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natural processes and technological applications, from atmospheric phenomena like rain clouds to industrial processes such as spray cooling of electronics. Due to their ubiquitous presence, droplets have
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) have shown promise in incorporating physical constraints into the learning process. Recent developments in geometric deep learning, graph NN and neural operators have further expanded the potential
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this paradigm to general history-dependent / rate-dependent behaviours still remains challenging and will be addressed in this project. The paradigm of model-free data-driven computational mechanics (DDCM
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the clinic and in silico. We focus on neurodegenerative processes and are especially interested in Alzheimer's and Parkinson's disease and their contributing factors. The LCSB recruits talented scientists from
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characterization: Using X-ray tomography, imaging analysis with classical or deep learning tools will be conducted to determine the binder's spatial distribution inside the pores. 1.2. Numerical Modeling
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. Such investigations rely on an original conjunction of experimental techniques and devices: magnetic resonance imaging, nuclear magnetic spectroscopy, confocal microscopy, optical tweezers, rheometry, acoustic
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. Integrated Platform Development and Pilot Demonstration - Design a prototype that combines energy harvesting modules with electroporation and ROS-based catalytic processes. - Optimize reactor design, including
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methods for processing, and analyzing. That is why, data-driven approaches are becoming increasingly popular in the localization and navigation domain due to their ability to address complex challenges