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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
. Description: The Ice Sheet and Sea Level System Model (ISSM) is an integral component of the Integrated Modeling Virtual Institute (IMVI), a recent NASA initiative aimed at synergizing models of the Earth
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analyze a suite of high-resolution regional ocean biogeochemical model simulations to provide actionable information to decision makers as part of NOAA’s Changing Ecosystems and Fisheries Initiative (CEFI
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large suite of cosmological simulations designed for multiwavelength cosmological modelling. Once in hand, the candidate will use the simulations to explore novel analysis methods with the goal
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simulations to identify key mechanistic drivers of viral persistence and immune response, and use SciML to automatically select ODE/PDE models that include these mechanisms. The postdoc will develop
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candidates will have strong past experience in scientific machine learning. Experiences in large language models, molecular modeling and simulations, and/or polymer science are preferred but not required
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Integrate models across platforms and workflows; manage inputs/outputs and ensure reproducibility Analyze simulation and experimental datasets; extract insights and quantify sensitivities and uncertainties
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experience in the following areas: Applied Machine Learning for Autonomous Systems: Experience developing and deploying ML models for perception, prediction, or decision-making in autonomous driving or robotic
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related field. Experience with finite element simulations and developing constitutive models. Knowledge of high temperature creep crack growth. Knowledge of engineering design codes such as the ASME Boiler
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atmospheric models WRF-Chem and/or CHIMERE, developing new descriptions of primary ice formation from sources such as aviation, wildfire emissions, and mineral dust. High-resolution simulations of selected case
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equations (SDEs) are widely used to model time-evolving phenomena in finance, biology, and social dynamics, the underlying data is often highly sensitive. This project tackles the intersection of complex