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correlations between active galactic nuclei, especially blazars, and neutrinos detected by KM3NeT. In this context, he or she will play a key role in the KM3NeT real-time data analysis group, as well as in
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stations for large-scale bioinformatic analysis, a cryo-EM microscope recently installed at the institute, as well as privileged access to state-of-the-art infrastructures: cryo-EM Titan Krios (ESRF
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significant part of the project will be dedicated to the analysis of the complex electrophysiological data. This analysis will be carried out in close collaboration with computational neuroscientists. Although
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | about 2 months ago
experience in soft matter and rheology or mechanics; fluent in English; taste for initiative; MSc thesis (or equivalent) completed Duration: 3 years, starting in autumn 2025 Locations: CEMEF (part of MINES
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Microelectronics teams, the PhD student will be supervised and helped. He/She will access, after training, the IEMN technological platforms. He/She will be provided the tools and computer accesses necessary
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therefore be part of a particularly dynamic research effort. As part of the JET2SB project, funds have been allocated for: - the acquisition of the computer equipment necessary for the research work
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collection of >6,000 isolates of the fungus present in the lab (and 20+ closely related species). Additionnally to computer analyses (which will represent the core of the project), the PhD student will
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particular NLP, statistical learning, machine learning, generative AI, and their major fields of application. Roles and responsibilities The applicant will join the team of the 3IA Côte d’Azur Institute and
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into **influence functions**, theoretical tools designed to quantify the impact of a sample on a machine learning model. These functions, defined through the derivative of model parameters or the loss function with
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the analysis of voting rules using robust and interpretable mathematical tools. It explores the writing of voting modes as the result of an optimization problem. Based on statistical depth functions