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. In this project, we aim to develop digital tools combining density functional theory (DFT) and machine learning (ML) to accelerate the in-silico design of solid catalysts for the DA process. - Perform
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therapeutic strategies. - DNA-protéines complexes modeling - Molecular dynamics simulations of biomolecules - Enhanced sampling techniques (Steered MD, Gaussian Accelerated MD) - HPC resources use - Scientific
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are nuclear physics, high energy physics, theoretical physics, astroparticles, astrophysics and cosmology, particle accelerators, energy and the environment and health. IJCLab has significant technical
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techniques, thermal mapping, power consumption analysis, electromagnetic emission patterns, etc. These measurements will be conducted in combination with an accelerated aging protocol. 3. Analysis of the trade
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, acceleration processes, and interactions with Mercury's surface and exosphere. A key emphasis will be placed on analyzing the three-dimensional distributions of the ions observed by the Mass Spectrum Analyzer
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while improving productivity, performance portability, scalability and resilience, performance and energy efficiency. The NumPEx Exa-DI project aims to improve and accelerate the development of exascale
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, electronic properties, and spectroscopic response. A major component of the project will focus on coupling DFT calculations with machine learning models to accelerate spectral prediction, identify robust