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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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of the Drosophila wing disc and observing their opening patterns, we can infer incompatibility. This will allows us to integrate insights from cell-level and tissue-level work into a 3D continuum model
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methods for causal inference. Nature Communications, 14(1), Article 1. https://doi.org/10.1038/s41467-023-37194-5 Delalandre, L., Gaüzère, P., Thuiller, W., Cadotte, M., Mouquet, N., Mouillot, D., Munoz, F
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analysis of data from the ATLAS experiment. The L2IT team plays a leading role within the ATLAS collaboration in the reconstruction of charged particle tracks using geometric deep learning (GDL). The person
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. - Experience in coding (python or other computer language). - Proven track record of publications in peer-reviewed journals. - English (written/oral) level of at least B2 (according to the common European
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experience with either in vivo extracellular electrophysiological recording or with in vivo fiber photometry; - have an academic track record proven by publications in the field of circuit neuroscience
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(fMRI), and eye-tracking measurements (main task) – Data analysis (main task) – Interpretation of results (main task) – Dissemination of findings through the writing of scientific articles (main task
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physics. • Strong academic track record and excellent interpersonal skills. • Ability to work effectively within a collaborative research environment. • Excellent command of English, both written and spoken
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The new rail line between Montpellier and Perpignan
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cataloguing of relevant case studies, combining satellite observations, reanalyses, and geostationary imagery to track the formation and evolution of cirrus under strongly perturbed conditions. Building