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phenomena at stake and the accurate prediction of such complex multi-phase, multi-physics system is then necessary to optimize the system parameters entirely. The first step consists in designing and
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data in order to predict the effects of ionizing radiation on living matter and to contribute to the development of innovative radiotherapies. These developments are carried out within a multi-scale
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better understanding of the molecular determinants governing protein targeting to the chloroplast and antimicrobial activity of with the aim to develop predictive models that can correctly identify
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and numerically predicting the infiltration of the final matrix by CVI. To this end, X-ray tomography acquisitions will be performed; the images will then be analyzed and processed to produce (i
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organ transplantation. HLA-Epicheck is a predictive model of the antigenicity of polymorphic amino acids on the surface of HLA antigens, relying on dynamic structural data. Four tasks are identified. Task
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Theory of Large-Scale Structure (EFTofLSS)—to include the effects of massive neutrinos and non-standard dark matter, validate theoretical predictions against simulated datasets, forecast expected
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missions within the framework of this ERC: i) to develop new models for the geometry of the cosmic web, taking into account the bias of baryons, and ii) to implement “nulling” techniques to predict the weak
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to compare theoretical predictions with experimental observations and measurements. - extend existing stochastic models and develop new models to understand actin dynamics in different contexts
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nanoparticles, whose manufacture is generally based on “trial & error” methods. Thus, the aim of TOSCaNA is to develop an experimental approach and a CFD formalism for predicting the size and morphology of metal
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via protein crystallography. - Development of a pipeline for protein design with existing software. These includes software for fold generation, sequence generation and structure prediction, and should