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Field
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- Interfacing machine learning with climate models Company: Princeton University Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in association with NOAA's Geophysical Fluid
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for climate-smart forestry. The project includes a collaboration with Dr. Laura Leites and Dr. Kim Steiner leveraging mature black walnut provenance trials and associated genomic and phenotypic data
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therefore quantify the effects of climate change on Earth on the motions of another celestial body (the Moon). This postdoctoral position offers the opportunity to collaborate with project scientists
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millennium, recent historical era and the coming centuries, using a combination of high-resolution climate modeling, machine learning/artificial intelligence (ML/AI) techniques, theory and observational
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-time opportunity for a Post-Doctoral Associate to work in the Climate Accountability Lab headed by Prof. Geoffrey Supran. The Post-Doctoral Associate will apply quantitative and qualitative applied
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to apply for a faculty or staff position using the Career worklet, please review this tip sheet . Position description: The Climate Accountability Lab headed by Prof. Geoffrey Supran at the University
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therefore quantify the effects of climate change on Earth on the motions of another celestial body (the Moon). This postdoctoral position offers the opportunity to collaborate with project scientists
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conduct research on the use of machine learning in ocean climate models. The goal is to demonstrate the successful use of machine learned parameterizations of unresolved processes that will reduce biases in
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The Environmental Institute (EI) at the University of Virginia (UVA) is seeking a postdoctoral Research Associate to join its Climate Fellows Postdoc Program. The selected candidate will work with
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of climate change and resulting human responses. Successful applicants should be skilled in one of two areas of research: 1) modeling of physical characteristics of extreme events (particularly heat waves and