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and output databases; deployment of methods and tools for data acquisition and visualization; * AI/Machine Learning/Deep learning techniques for model input and output data analysis and production, in
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. The approach used relies on developing machine-learning interatomic potentials based on ab initio calculations, which are then employed to perform large-scale classical molecular dynamics simulations. However
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to collaboratively train machine learning models without sharing their data. Instead, clients exchange local model updates with a central server, which uses them to improve a global model. While this paradigm enhances
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experimentation with innovative modeling, data analysis and machine learning/AI techniques. 1 - Global Energy-Economy-Environment Systems Modelling Your main duty is to contribute to our collection of linear
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range of computer vision tasks. Their strong representational capacity, however, comes at the price of significantly higher computational complexity and memory requirements. This poses a major challenge