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. This project will rely on recent advances in neural networks to develop machine learning potentials (MLPs) for MD simulations of realistic nanomaterial/coolant-liquids and use these to gain fundamental insights
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Transactions on Probabilistic Machine Learning. A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, L Kennedy, J Gabry, PC Bürkner, M Modrák (2020). Bayesian Workflow. B Carpenter, A Gelman, MD
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, artificial intelligence/machine learning, digital twins, and blockchain technology for operations and maintenance. This position is part of the RESTORE project, which aims to develop, test, and deploy
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learning. The project involves a collaborative team, including a postdoctoral researcher and a PhD student, with specific objectives: Define and acquire a comprehensive database of high-quality video priors
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robotics, and materials science. Project description: 3D-printing of soft robotics is a growing field, with many applications in biomedical devices, electronics, and autonomous machines. Actuators to drive