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of an iPSC model of mutations observed in patients - Characterization of defects at the cellular level - Characterization of defects at the transcriptomic level The successful candidate will work in the “mRNP
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modeling), and stem cell biology (reprogramming and differentiation) are paving the way to new concepts that will undoubtedly improve skeletal regenerative strategies. Our strong and recognized expertise
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and process behavioral and electrophysiological data • Model behavior based on diffusion models and make explicit link with neurophysiological data • Conduct detailled statistical analysis • Write
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teams to contribute to the development of fundamental aspects of computer science (models, languages, methods, algorithms) and to develop synergy between the conceptual, technological and societal
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. Chem. Int. Ed. 2024, 136, 16, e202400992. 6. A. Lachguar; T. Neumann; A. V. Pichugov; E. Jeanneau; L. Veyre; C. Thieuleux; C. Camp Dalton Trans. 2025, 54, 3804–3811. -Synthesis of molecular complexes
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, advanced co-culture organoid assays, and in vivo models to decode the mechanisms underlying CAF-driven CRC evolution. Access to single cell RNA sequencing and spatial transcriptomics data from active
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and physics, Materials Mechanics, Geotechnics, and Civil Engineering Proven skills in laboratory and/or field experimentation Potential aptitude in numerical modeling Ability to work in a team and in
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, we propose to investigate a new approach that combines the benefits of a molecular alphabet extension with those of modifying the topology of the DNA sugar-phosphate backbone. Our model will be based
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. Analysis of experimental characterization will be assisted by numerical simulations using in-house multiscale models of solidification. Main Activities Design and development of experiments. Characterization
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- Conduct remote sensing analyses and spatial modeling of grassland ecosystems - Supervise water sampling and organize field logistics in collaboration with students and partners - Integrate ecological data