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particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required skills : We
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using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
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. CESBIO is organized into two research teams (modeling and observation systems) and maintains a strong international outlook through collaborations and missions abroad. Where to apply Website https
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the framework of the ANR EmergeNS whose aim is to understand, through mathematical and computer models, the role that autocatalysis, multistability and spatial heterogeneity may have played in the emergence
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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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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Graphab is a graph-based software to model
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this, the postdoc will use innovative modeling based on the coupling of (1) a meteorological model adapted to the fine spatial scales of these systems and explicitly simulating turbulent structures, and (2) a
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sophisticated mouse genetic models of cancer and conditional gene targeting, single-cell RNA-seq, spectral flow cytometry, multiplex imaging and spatial genomics data acquisition and analysis. Where to apply E
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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melt than greenhouse gas emissions. - The high-resolution regional atmospheric chemistry-transport model CHIMERE will be used to understand the impact of terrain complexity and the spatial variability