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, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
interactions. Education and Experience: Fundraising experience: Seven or more years. Experience in a research university or similarly complex institution: A minimum of four years of fundraising. Knowledge
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to their culture and pay our respects to their Elders past and present. View our vision towards reconciliation . Role highlights An on-site key role at a world-renowned facility supporting NASA’s Deep Space Network
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Artificial Intelligence (AI) services in Internet of Things (IoT) networks, where latency and timeliness are paramount. The successful candidate will be responsible for the end-to-end investigation of novel
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, enjoy tackling complex multi-physics problems, and have the drive to explore innovative concepts at the intersection of engineering, data, and emerging technologies. DTU Wind and Energy Systems, in
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Are you ready to dive into the fascinating world of resilient optical transport networks? We're on the lookout for a talented Postdoc to join our dynamic, international team at the Optical Networks
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safer, more reliable, and more sustainable renewable energy systems. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods
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, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery, enjoy tackling complex multi-physics problems, and have the drive to explore innovative concepts
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. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods, machine learning tools, and simulation techniques. If you thrive
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description At PRISMM , we enjoy analysing biomarkers of exposure and effect in complex samples using mass