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research. The project will provide opportunities for collaboration on high-impact publications, networking with leading experts in business power and public policy, and participation in international
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, graph neural networks) to match questions to relevant geodata workflows; integrate semantic web technologies (e.g. RDF, SPARQL, OWL), large language models and graph neural networks into the reasoning
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of ecosystems. The project aims to: Improve our understanding of what controls net primary production of ecosystems. Develop upscaling methods to estimate whole-ecosystem transpiration from local measurements
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transpiration of ecosystems. The project aims to: Improve our understanding of what controls net primary production of ecosystems. Develop upscaling methods to estimate whole-ecosystem transpiration from local
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of large strain (antigenic) diversity, network descriptions of strain structure, and implications for resilience to perturbations. We are also more generally interested in extensions of this work to other
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-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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health. But, we are always open to embrace new approaches! Together with industrial leaders and an extensive network of clinical institutions, we cover the entire trajectory from modelling a given subject
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oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover
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infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active