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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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Position Details Position Information Internal Posting? Posting Number SP005014P Position Title Postdoctoral Research Associate, Statistical and Computational Modeling for Digital Twins Division
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of the time could be used to check and update the GRAVITY and MATISSE noise models. The application to real data will imply data processing of VLTI and ERIS data Specific Requirements Required skills
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complements the strengths of Texas A&M AgriLife Research unit at Corpus Christi in Digital Agriculture. The incumbent is expected to work with a team of transdisciplinary scientists to develop predictive models
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candidate will join Dr. Siddharth Saksena’s research group, which focuses on advancing hydrologic modeling, flood forecasting, and hydroinformatics through the integration of artificial intelligence, physics
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to fit Ca profiles in olivine and calculate associated cooling rates, 2/ an analysis of uncertainty propagation for these models, and 3/ a global unified database of existing data that could be used
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resilient and meet regulatory demands, using system modeling and scenario analysis. Job description Supply chains are increasingly exposed to complex and overlapping pressures. Climate change, geopolitical
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or more senior research positions to analyze and model the delivery of clean energy and industrial decarbonization infrastructure associated with net-zero transitions. The role will report to the Andlinger
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Inria, the French national research institute for the digital sciences | Bures sur Yvette, le de France | France | 6 days ago
physiological and neural recordings (EEG, fNIRS, ECG, blood pressure, and PPG) with advanced signal processing, mathematical modeling, and artificial intelligence. This project aims to provide new insights
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implementation and data handling; iv) contribute to the intercomparison with simulations and outputs of one model (CISM); v) collect, organize and quality check output data from the participating modelling groups