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tract. We aim to develop human 3D tissue models that mimic the mucosa lining the airways and the pulmonary alveoli. These models will provide the means to identify the determinants of susceptibility
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will apply and develop computational tools for the analysis of large data sets generated by short-read, long-read, and single cell DNAseq/RNAseq analyses of cells evolving in vitro in culture and in vivo
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system (https://research.pasteur.fr/en/team/cell-death-and-epithelial-homeostasis/). We use a wide range of live imaging technics and develop new tools (including live sensors and optogenetics) to dissect
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. Through this project, the applicant will be able to develop their knowledge in genetics, gene regulation, and epigenetics. The project will involve communicating and learning from clinician researchers who
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these behaviours or to challenges in detecting them. We aim to develop a Bayesian Program Synthesis8 (BPS) methodology for producing synthetic data that mirrors key characteristics found in experimental recordings
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-electron tomography combined with semi-automated cryo-FIB/SEM lamellae. Develop fluorescence high-resolution live imaging for the model bacterium V. parvula in strict anaerobia conditions. Phenotypically
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inference necessitates simultaneous inference of particle localizations and model parameters, which can lead to substantial bias. To overcome this, the successful applicant is expected to develop a Markov
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distribution of microcircuits affect the mesoscopic, or modular, structure of a network [8]. Generative modeling of biologically-plausible brain networks from learnt latent embeddings. This axis aims to develop
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particles driven by Brownian noise at different temperatures, the intern will develop a spectral Bayesian2–4 approach to reliably detect out-of-equilibrium dynamics from the trajectory of a single particle5