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Sorbonne Université | Villefranche sur Mer, Provence Alpes Cote d Azur | France | about 2 months ago
imaging instruments and high throughput genomics that informs advanced numerical analysis methods (modeling, statistics, machine learning). Plankton encompasses all organisms roaming with marine currents
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such as water-in-salts is not correctly captured by simple analytical interatomic potentials. For these reasons, we propose to deploy a machine learning approach to accelerate our simulations. The aim
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network management and efficiency. Methodology The research plan considers a range of Machine Learning (ML) solutions to address the challenges of predictive analysis in dynamic contact networks
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