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for a short-term 2.5-month postdoctoral position (full-time) focused on developing and validating machine learning models that predict soil health and crop performance. The position will exploit datasets
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Position Details Position Information Internal Posting? Posting Number SP005013P Position Title Postdoctoral Research Associate, Predictive Modeling for Mental Health Outcomes Division/College
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the 1990s, continuing its theoretical development and application for ocean forecasting and climate predictions. NERSC leads DA development in the Norwegian Climate Prediction Model (NorCPM), which delivers
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Argonne National Laboratory, in the Applied Materials Division, has an immediate opening for a postdoctoral appointee. The candidate will develop physics-based models to predict the structure and
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machine-learning methods to weather forecasting, climate analysis, or spatial data. Strong background in spatiotemporal modeling, probabilistic prediction, or time-series analysis. Proficiency in Python and
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 1 day ago
transformed into heterogeneous graphs, where rows become nodes and primary–foreign key relationships induce edges. GNNs can then propagate information across the relational structure and learn predictive
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models; predicting density and uncertainty surfaces from those models; evaluating predictions with contemporaneous data not included in the models as well as knowledge from the literature; and
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Weather and climate prediction are undergoing a profound transformation. Alongside traditional physics-based forecast systems, machine-learned (ML) weather prediction models, hybrid ML-physics
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data to learn contextual representations of microbes and communities and translate them into predictive models for successful crop microbiome engineering. Your job Plant-associated microbiomes can
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microbiome and genome data to learn contextual representations of microbes and communities and translate them into predictive models for successful crop microbiome engineering. Your job Plant-associated