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are widely used in modern life due to their strength and durability, with applications ranging from construction to packaging. However, their long-lasting nature also poses environmental challenges, as they
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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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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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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
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by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The successful candidate will use the poroelasticity models developed in the M3DISIM team
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of new electronic and structural properties, which will be explored in the context of neuromorphic applications. The successful candidate will be responsible for: • Fabricating heterostructures by pulsed
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coefficients, and structure–property relationships. • Collaborate closely with experimental partners for model validation. • Contribute to publications, reports, and dissemination of project results
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and assembly) (3) the study of their structure and their properties and (4) analytical and numerical modeling. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5031-CORAME0-048
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for: • Contributing to various tasks related to the modeling of lipids and membrane proteins involved in lipid droplet biogenesis. • Developing and implementing the POP-MD algorithm in the OpenMM software
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objective of the successful candidate will be the implementation of advanced fast MAS solid-state NMR, and also the set-up of DNP approaches. The goal is to study structures of the viral membrane-bound