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. SILEX 2025) to calculate the Fire Radiative Power (FRP) and compare with satellite observations (VIIRS, SLSTR, FCI). Develop a fire front segmentation algorithm using machine learning techniques (deep
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 16 hours ago
supermassive black holes through a combination of observational data, machine learning techniques, and cosmological simulations. The group is actively involved in multiple JWST Guaranteed Time Observation (GTO
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
for extension based on mutual interest. We are looking for individuals with a strong theoretical and practical background in large language models, machine learning, and natural language processing, combined with
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research project Expertise in machine learning Additional expertise in one or more of the following: digital signal processing, statistics, multimodal processing, FAIR data management, music theory
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laboratory-based research with large-scale trials in real production environments to develop globally applicable solutions that reduce food waste and enhance shelf life. Subject description Fruit and
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collaboration with colleagues in the John Radcliffe Hospital and the Oxford Big Data Institute, with the central aim being the development of rapid diagnostics of antimicrobial resistance in clinical samples. You
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-renal diseases. Our research spans large-scale register and laboratory data, causal and predictive modeling, and computational image analysis of kidney biopsies. About the Research Group: Led by Professor
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postdoctoral associate positions, starting immediately. Dr. Liu has extensive experience in big data analytics, systems biology, probabilistic graphical models, causal inference and machine learning. Dr. Liu's
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and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning