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over the course of the project. References: - Deneu B et al (2021) Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment. PLoS Comput
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research is based on recognized expertise in synthesis, structural and chemical characterization at the nanoscale, micro- and nanomagnetism, spin dynamics, and atomic-scale modeling. Where to apply Website
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power of NNs with the ability of LMMs to robustly learn from structured and noisy (non i.i.d.) data, applying them on the prediction of both plants and human phenotypes. These models will combine
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of the variability and uncertainty of simulated outputs • an explicit quantification of prediction error • an interpretable and controllable structure (e.g., Gaussian processes, …) 2. Model industrial system
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epitaxy and of characterizing their structural, morphological, electrical and optical properties, assessing in particular their stability under ambient conditions. Once the growth halide perovskites
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) represent a major source of intoxication. These compounds are often deliberately introduced in natural environments and are mainly associated with intensive farming and soil overexploitation agriculture
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of understanding cirrus clouds in climate studies. We are seeking postdoctoral researchers to contribute to our mission of advancing knowledge on how aerosols influence cirrus formation and evolution under both
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of understanding cirrus clouds in climate studies. We are seeking postdoctoral researchers to contribute to our mission of advancing knowledge on how aerosols influence cirrus formation and evolution under both
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extended complexes) The application to various models of MHD and flows in porous media The numerical analysis of the schemes The development of the computational kernel of the NEMESIS software library
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Structures team, which specializes in the observation and modeling of tectonic processes, from grain to lithospheric scale, and from seismic cycles to the growth of major geological structures. The research