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Field
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The Duarte Group works at the forefront of computational chemistry, developing predictive tools for reaction modelling and molecular design across catalysis, sustainability, and health. Alongside
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. Furthermore, a novel predictive algorithm of School-age neuropsychological outcome will be developed combining radiomic model of brain development, with qualitative neonatal MRI findings. Achievement
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, manufacturing) by creating applications for critical systems, adaptive and autonomous systems, advanced perception, diagnostics, quality control, and prediction systems. Further research areas include precision
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 8 hours ago
traditional predictive attempts and limits the availability of training data for high-resolution atmospheric and hydrological models. This limitation is compounded by the fact that many atmospheric reanalysis
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 9 hours 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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programs-ranging from national infrastructure to major technological rollouts. The project focuses on developing intelligent decision architectures, predictive analytics, and adaptive computational models
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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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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methodologies, advanced controller synthesis, performance and stability assessment. Trade-off, prototyping and selection of advanced DFAOCS control methodologies: minimum set to be explored: model predictive
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regression to represent unknown dynamics for model predictive control. Despite the practical success, there are still many theoretical open questions regarding scalability, uncertainty bounds and deriving