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AgriLife and make a difference in the world! Position Information: The successful candidate will contribute to developing and evaluating terrestrial and aquatic nitrogen dynamics and emission modeling, with
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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. Washington Monthly Magazine ranks FIU among the top 20 public universities contributing to the public good. Postdoctoral Associate in Vegetation Dynamics Modelling at Institute of Environment Position
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the supervision of Dr. Joseph Kwon. We’re seeking a creative Postdoctoral Scholar to join our team and advance cutting-edge multiscale and hybrid modeling—integrating first-principles simulations with
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, combines advanced system neuroscience and computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models
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earth system model data, with an emphasis on Seamless System for Prediction and EArth System Research (SPEAR) for seasonal to multidecadal prediction and projection. The project will emphasize elements
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specializing in hydrologic modeling, water quality, carbon dynamics, and CO2 and CH4 emission modeling. The successful candidate will contribute to developing and evaluating aquatic carbon dynamics and CO2 and
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
: 271598471 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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science, or in a related field Required Related Experience Computer programming, statistical modeling Required License/Registration/Certification None Physical Requirements Sitting for extended periods of time
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, graph neural networks) to match questions to relevant geodata workflows; integrate semantic web technologies (e.g. RDF, SPARQL, OWL), large language models and graph neural networks into the reasoning