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on protein stability and activity. However, the expression systems traditionally used in laboratories and industry for protein expression are still unable to accurately reproduce this natural process
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laboratory team is likewise highly recognized for its research in computer vision and neuro-inspired artificial learning. Both teams have been collaborating for four years on projects at the interface between
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capacity to engage in interdisciplinary scientific discussions (with biologists, biophysicists, computer scientists, etc.). Applicants must hold a Ph.D. degree and hands-on experience in cell/tissue culture
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using the KM3NeT detectors • Data analysis from SVOM instruments as well as images from the COLIBRI telescope • Participation in KM3NeT shifts and service tasks (calibration, construction, processing), as
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Ecological Processes (BIOECO)” research group, which brings together ecologists. Their research addresses questions aimed at limiting biodiversity loss in different contexts, including ecosystems invaded by
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to develop chiral metal nanoclusters, understand their chirality at the atomic level through a combination of advanced spectroscopic techniques and theoretical simulations, and apply them to relevant processes
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adipose tissue. In particular, we will study the role of different membrane receptors and their signaling pathways in the browning process. The various techniques used will include cell biology and genetic
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turbulent plasmas and by phenomenological models. The overarching goal of this ambitious programme is to describe the acceleration process across length scales, in the turbulent flow, in the inner jet and in
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of definitions, theorems and proofs. We would like to apply this to make the use of computer formalisation practical and current for mathematical research writing. Where to apply Website https://emploi.cnrs.fr
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composition of lipids and proteins. Importantly, lipids and proteins are not static, they diffuse due to thermal agitation and can be actively reorganized by cellular processes. This dynamic heterogeneity