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://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed by the team: https
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electronic components are necessary. Thus, new components are developed from gallium nitride (GaN) to manufacture fast switches and rectifiers that can withstand high voltages for reduced component sizes
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the genetic material of incipient species can dissolve species boundaries, a thorough comprehension of the evolution and regulation of meiotic recombination during the speciation process is central to our
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. The LRGP develops the scientific and technological knowledge necessary for the design, study, management and optimisation of complex physico-chemical and biological transformation processes involving matter
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the developing cortex and play a crucial role in establishing proper cortical regionalization and lamination. Distinct CR subtypes are generated at signaling centers in response to morphogens and participate
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signalling center origins - To work on the molecular profiling of tissues and cells from human stem cell-derived brain models - To develop molecular insights about key morphogenic pathways responsible
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lining of blood vessels— which plays a central role in the development of vascular diseases. Blood vessels further complicate this picture through their complex geometries, featuring diameter variations
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waste, biomass byproducts, nitrogen oxides, etc.) into valuable chemicals and developing renewable hydrides, with the goal of closing the carbon and nitrogen cycles and promoting a circular economy
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coordination of activities carried out by PhD students and technical staff • Supervision of the development of protocols in microbiology and molecular biology • Participation in field experiments and in
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the field of optics and photonics. The team is working in the Photonic axis and is developing novel optical imaging techniques for biology. In particular, Pierre Bon is developing novel label imaging