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to develop an aeromedical dispatch management software as a technology hub that provides data-driven prediction model and an automated dynamic decision model. The successful candidate will be responsible
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computing. This particular position focuses on time-series analysis and forecasting using transformer based foundation models. About the Project Time-series prediction using transformer based models is
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physics-integrated machine learning models—to predict, analyze, engineer, and understand microbial community dynamics. Applications span precision medicine and built environment microbiomes, with a strong
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intelligent decision architectures, predictive analytics, and adaptive computational models that can operate in dynamic, uncertain, and high-stakes project environments. The appointee will conduct original
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 hour ago
. Description: Biospheric modeling --- This postdoctoral position focuses on advancing our understanding of Earth's biosphere and complex feedbacks to weather and climate through the innovative integration
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predictive models for failure control. Validation & Experimental Collaboration: Compare simulations with experiments, collaborate on proof-of-concept testing, and refine models based on results. Where to apply
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refines algorithms and workflows for crop and pasture monitoring, modeling, prediction, and decision support and automation; Supervises graduate research assistants and student interns working
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inviting dynamic young scientists, capable of theoretical fracture mechanics and related modeling techniques, to join our team to probe cutting edge issues in fatigue and fracture. Some examples of research
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-driven methods provide excellent performance under low or cyclo-stationary regimes but struggle with highly dynamic and rapidly varying conditions; conversely, model-based state observers ensure robustness
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Scholar (FP01) – AI Imaging & Retinal Disease who is interested in ophthalmology to assist in refinement of AI models as well as validation of new biomarkers and data analysis to be able to predict whether