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simulation of turbulent reactive flows. Modeling and simulation of turbulent flames in distributed combustion using a hybrid RANS/LES approach. Develop, implement, and test models for the numerical simulation
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capacity, ....). - build codes to generate different type of distributions (Poissonian, hyperuniform and aggregated distributions), either on a planar or curved surfaces - use codes based on coupled dipole
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vision researchers to design algorithms specifically tailored for the extraction and analysis of these historical diagrams. EIDA considers these diagrams both as visual heritage and as tools
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evaluation of algorithms for: perception in robotics; sensor based control and navigation ; interactive mobile manipulation; multi-sensor data modelling and fusion. This job offer takes place within
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. The second part of the mission concerns a research project focused on polymer foams (60% of the time). This project aims to understand how the distribution of solid material between cell walls and struts can
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properties are optimized by machine learning algorithms to retrieve properties of reference flames gathered in a learning base. A virtual scheme consists of a main block that models the heat release from
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and homeostasis, as it regulates the distribution of cell fate determinants in asymmetric divisions. In the model system Drosophila neural stem cells (NSCs), it has been established that cortical
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, data-driven algorithms, deep reinforcement learning The Pprime laboratory is a CNRS Research Unit. Its scientific activity covers a wide spectrum from materials physics to mechanical engineering
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spatial and seasonal distributions of PFAS and identification of the key processes controlling their fate (dispersion, transformation, sediment retention). Contribution to modeling PFAS transport in
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enables high activity in olefin polymerization, while providing precise control over composition and molecular weight distribution. However, this activator remains a poorly defined solid at the structural