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Duties/Responsibilities: Synthesize, harmonize, and analyze large environmental monitoring and remote sensing datasets from coastal Louisiana Train and apply multimodal and generative AI methods to predict
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of large-scale geospatial and time-series datasets. The candidate will develop and evaluate multimodal AI models to characterize vegetation and land-surface dynamics and quantify ecosystem responses and
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materials. These systems are instrumented and connected through a unified digital thread platform that captures multimodal, high-frequency data across the full manufacturing lifecycle, from process execution
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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data