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of national research infrastructures Evaluating the evolution of Generative AI performance over time and across tasks Analyzing international AI models and their representations of the U.S. in global discourse
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based on predictions from statistical and machine learning models Postdoctoral scholars are represented by UAW 4121 and are subject to the collective bargaining agreement, unless agreed exclusion criteria
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land use-fire regime relationships Contribute to the development of predictive models for future fire risk under various climate and land use scenarios This position offers an exceptional opportunity
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simulation models to analyze, predict, and optimize water distribution networks. Engage in state-of-the art research on lithium supply chain dynamics, forecasting potential bottle-necks, and proposing
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of the following: Ecosystem Modeling, Machine Learning, Microbiome, Microbial Ecology, Soil Science, or Computational Biology. The positions are for several different projects, including the following: (P1
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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in Agriculture • Machine learning models for pest and disease prediction • Crop classification using multispectral imagery • Digital twin models for farm simulation and management • Collaborate with
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focus in machine learning. The postdoctoral scholar will work on topics of mutual interest such as, but not limited to, automatic machine learning model selection and automatically explaining machine