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molecular simulations, machine-learning techniques, and statistical mechanics for research opportunities in: Development of data-driven schemes for the discovery of slow degrees of freedom Molecular
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Postdoctoral position (M/F): Machine learning design of alloys for concentrated solar energy storage
mission will be to develop machine learning models to predict properties of alloys of elements of groups 1 to 15, such as their melting temperature, range, and enthalpy. Based on these predictive models
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omics tumor profiles, and proceed by sophisticated machine learning approaches as well as biological network modelling. At Institut Curie our situation is ideal to pursue these goals, since the choice
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with interests in molecular simulations, machine learning, and statistical mechanics for research opportunities in: • Development of data-driven schemes for the discovery of slow degrees of freedom
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leader. It aims to automate construction machines to increase their efficiency and reduce their carbon footprint.The aim is to equip these machines with sensors enabling them to analyse their environment
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., Nature Communications (2020) 11:4691] based on an analysis of local atomic environments using “machine learning” methods (MiLaDy). In parallel with this analysis of the database, and to have a better idea
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generation dual species Rydberg quantum computer with >400 fully addressable qubits for scalable digital QC (aQCess - Atomic Quantum Computing as a Service) currently under construction. For more information
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Council. He or she will gain expertise in multi-scale molecular dynamics simulations, enhanced sampling techniques and application of machine- learning techniques to analyze simulation data, all applied
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the limits of the scale in force. Mission confiée The main objective of this project is the understanding and development of robust and effective stochastic optimization methods for training deep learning
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generic approach allowing the accurate, robust, and fast simulation of the optimal fracture reduction strategy whatever the type and class of the fracture. Combined approaches exploiting both Deep-Learning