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Director, Illinois Three-Dimensional (3D) Mesonet - Illnois State Water Survey, Prairie Research Ins
Director, Illinois Three Dimensional Mesonet Illinois State Water Survey / Department of Climate, Meteorology & Atmospheric Sciences Prairie Research Institute University of Illinois Urbana
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
and AI-driven Integrity in Mitigation. CLAIM advances the credible use of artificial intelligence, especially generative AI and large language models (LLMs), to accelerate climate mitigation while
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
. CLAIM advances the credible use of artificial intelligence, especially generative AI and large language models (LLMs), to accelerate climate mitigation while safeguarding integrity in climate commitments
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to the design and updating of contents, methodologies and pedagogical models for professional sectors affected by climate change (A4.2). Development of innovative teaching tools, pedagogical kits and guides
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while simultaneously creating lab climates in which everyone can thrive and benefit from their leadership and inclusive mentorship. Located on the Davis campus in the Departments of Physiology & Membrane
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, length of stay management, denial prevention, and performance improvement initiatives. This position provides direct oversight, serves as a role model and primary resource to coworkers and others
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systems planning, length of stay management, denial prevention, and performance improvement initiatives. This position provides direct oversight, serves as a role model and primary resource to coworkers and
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different scales, with the aim to improve our understanding ofthe role of snow in the climate system. Within our Snow Physics group, we are looking for a Postdoc in "Improving understanding & model
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(ILL). The current ML models are optimized mainly for (monochromatic) X-ray reflectometry. We aim to generalize this approach to a wide range of samples and time-of-flight NR, coupled with automatic data
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crane. The successful candidate will build reproducible machine learning pipelines, integrate detections into spatial ecological models, and generate conservation-relevant outputs for regional partners