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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
: 277494287 Position: Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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, investigating (a) cumulative environmental impacts, (b) the use of census microdata for social vulnerability modeling, and (c) population and built environment exposure to climate hazards. The broad agenda
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vulnerability modeling, and (c) population and built environment exposure to climate hazards. The broad agenda of this research is assessing the fitness of geospatial indicators to inform conceptual and policy
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incident angles for benchmarking and validation of theoretical calculations and computational physics and chemistry modeling of important surface processes occurring at plasma-material interfaces in fusion