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Postdoctoral position (M/F) on impedance and dielectric study of solid/solid interfaces in batteries
, tortuosity, additives amount…). On another side EIS is particularly interesting since it is a non-destructive investigation method, giving access to several electrochemical parameters of major interest in
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subpopulation in vitro by potential therapeutic agents. Institut Cochin is a biomedical research center located in the center of Paris (22 rue Méchain),, 75014 Paris). It is affiliated to INSERM, CNRS and
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, visit https://www.biocean5d.org/ . The applicants will work on close collaboration with Jose M. Montoya, from CNRS. - Developing analytical theory and/or simulation models on the relative importance
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values foster the professional development of its staff—key contributors to collective success—as well as the growth of the laboratory itself. Where to apply Website https://emploi.cnrs.fr/Offres/CDD
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of the project MESSENGER: « Can rock-powered Microbial EcoSyStEms provide valuable iNsiGhts into early life and its emERgence? » funded by the PEPR ORIGINS (https://pepr-origins.fr/en/ ) and integration
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Postdoctoral Opportunity in Molecular Biology to Model the Progression of Rheumatoid Arthritis (M/F)
the DigiTREAT project (PEPR Digital Health), which aims to model the progression of rheumatoid arthritis and its evolution in the presence of drug treatment. As part of this project, the postdoctoral researcher
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layered semiconductor characterized by an anisotropic crystalstructure and quasi-one-dimensional ribbon-like morphology. Its electronic structure is predicted to host relatively flat bands associated with
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• Establishment of optogenetic systems: development and validation of an Opto-TBRA system for its controlled activation. 4. Analysis of collective behaviors • Real-time imaging: Use of confocal and multiphoton
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in cancer cell signaling. The host team has demonstrated its immunomodulatory role in cutaneous melanoma, and this project aims to evaluate its potential as a therapeutic target. o Perform xenografts
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. The work will be primarily computational, focusing on the development of deep neural network model architectures and their training. It will involve extending the preliminary results we have already obtained