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Field
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving
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applied research on AI-driven and AI-enhanced industrial energy systems optimization modeling, material flow analysis, and supply chain analysis of industrial commodities and critical materials
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-driven mathematical modeling in a transdiagnostic clinical cohort. https://impact-mh.org/awardees/impact-mh/ IMPACT-Y is collecting repeated measures from approximately 2,400 individuals across multiple
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. The lab is seeking Posdoctoral Associate who are passionate about discovery, driven by scientific curiosity, and eager to make meaningful contributions to women's health. While technical expertise is
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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combining artificial intelligence with human expertise. The lab develops knowledge-grounded artificial intelligence, text mining and knowledge assembly, mathematical and systems modeling, and causal analysis
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-driven research questions, evaluate models rigorously, and communicate results through scientific writing and presentations. Demonstrated ability to connect data analysis and modeling assumptions
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring
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About the Opportunity Postdoctoral Associate – Gene Therapy and Transport Modeling Bajpayee Lab at Northeastern is seeking an exceptional Postdoctoral Associate to lead high-impact research in
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 15 days ago
inform representations and encoder adaptations. This activity will provide hands-on experience in making three-dimensional vegetation structure accessible within data-driven geospatial modeling processes