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tools on real data will allow a better understanding of gas dust and dusty-wind CND interaction, the use of resolved dust structures to constrain the BLR geometry and eventually improved modeling of BLRs
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, residents). RMeS is structured around 2 independent research teams: REJOINT (formerly STEP) and REGOS (see organizational chart ). These 2 teams still benefit from our 4 open technological platforms: SC3M
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. Tasks 1. Modeling and analysis of uncertainties The first phase of the research will focus on identifying, structuring, and integrating major sources of long-term uncertainty that influence strategic
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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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data Proficiency in advanced statistical analysis methods: structural equation modeling (SEM), robust Poisson regressions Proficiency in handling non-response: weighting and multiple imputation
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-effectively integrated into advanced technology nodes for sensor, nonvolatile memory, logic, and neuromorphic applications. Currently, hafnium-zirconium mixed oxide (HfxZr1-xO2) offers the widest stoichiometry