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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 8 hours ago
-resolution fuel maps, and apply explainable AI techniques to interpret model behavior. These fuel products will be coupled with sstochastic fire spread simulators to quantify wildfire behavior (e.g., burn
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manager and maintain regular communication with all other relevant stakeholders. Where to apply Website https://utc.recruitee.com/o/chercheur-contractuel-fh-modeles-predictifs-securit… Requirements Research
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to lead an investigation exploring the ability of recently developed global earth system models to simulate coastal sea level across sub-annual timescales. This work will leverage a suite of coupled models
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limitations in both measurement and modelling techniques. Current in-process measurement methods are restricted to surface-only monitoring devices (e.g., cameras and pyrometers), which fail to capture
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partner from data sciences provides data management and AI based Image analysis, an internal simulations group working on quantitative models to reproduce and predict experimental data, and an internal
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Team : We seek a researcher with demonstrated experience in perturbative modeling of LSS (in particular biased tracers of dark matter), analysis of simulated datasets, and strong programming in Python
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://www.esa.int Field(s) of activity/research for the traineeship The proposed training project consists in one or several of the following tasks: On the Power Systems area: Build generic simulation models
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Theoretical Quantum Many-body Physics and Quantum Sensing at Indiana University Bloomington Fields: Quantum many-body theory, AMO–condensed matter interfaces, advanced numerical simulations, quantum sensing
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policy. Dr. Kang’s research laboratory is focused in personalized testing pathways, translation of diagnostic innovations, and cancer screening. We develop predictive models, simulation frameworks, and AI
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic