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successful candidates will dedicate their efforts to the following specific research objectives: (1) Developing models for predicting the thermal runaway (TR), venting, and jet fire in a single cell with
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engineering for mobility platforms • AI/ML for transportation prediction, system optimization, and environmental/health impact modeling • Deployment of decision-support tools for public-sector clients
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, we aim to create autonomous “self-driving” microscopes that: build statistical models of biological dynamics in real time predict the most informative next experiment execute it automatically on living
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optimisation. State-of-the-art digital models and AI tools that incorporate machine learning could enable predictions of the dry fibre forming that are subsequently used as input into the RTM process model
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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supplying high-quality data needed to validate and refine the next generation of predictive numerical models. A key innovation in this research will be the use of transparent soil analogues of sand and clay
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well as predictive models based on machine-learning technologies, in order to carry out code development and testing activities within the listed projects; therefore, skills in software design and development
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 2 hours ago
system. Climate models are important tools for improving our understanding and prediction of atmosphere, ocean, and climate behavior. We seek candidates with an interest in advancement of radiative
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—these approaches can recover unmeasured near-wall structures, improve subgrid-scale modelling, and enhance predictive accuracy. Possible project directions include: 1. Reconstructing near-wall velocity fields from
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and refine the RG-based model to enhance its biological interpretability and robustness across different tumor types; to extend the model to simulate and predict solid tumor response to innovative