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Field
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dynamic network of researchers in purpose science across institutions who desire meaningful opportunities to engage with other scholars, youth-serving organizations, and youth themselves. Ke y
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Overview: As data becomes more accessible, new challenges arise around how best to use it—especially in complex, multi-system environments like aerospace. Ontologies offer a powerful solution by
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, which rely on rigid links and localized interaction points, soft robots are composed of deformable materials that can conform to complex geometries and operate safely around humans. They offer unique
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of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical
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processing approach based on flow patterning to make meter scale LCEs of complex shapes and actuation modes. ALCEMIST builds on a tight synergistic collaboration between the Experimental Soft Matter Physics
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technical complexity; networks and cross-boundary information and knowledge sharing; policy problems associated with governance, privacy, and information access; burgeoning information types, uses, and
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, Heidelberg and Mannheim, our researchers harness interdisciplinary collaboration to decipher the complexities of disease at the systems level – from molecules and cells to organs and the entire organism
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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trunk around an object. Unlike traditional robots, which rely on rigid links and localized interaction points, soft robots are composed of deformable materials that can conform to complex geometries and
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strong interest in animal behaviour and insect ecology. Specific requirements are: Strong analytical and quantitative skills, with the ability to work with complex behavioral datasets Proficiency in