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Additional Information Eligibility criteria The researcher should have the following skills: - demonstrate excellent teamwork and communication skills, - be strongly motivated to conduct high-impact applied
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regimes; and machine learning, capturing complex nonlinear behaviour at the cost of model opacity. BENEFIT synthesises these paradigms by integrating stability analysis directly into machine learning
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the CNRS Institute of Humanities and Social Sciences and is primarily affiliated with CNRS Section 34 (Language Sciences) and secondarily with CNRS Section 26 (Cognition, Brain, Behavior) of the CNRS
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material for an intended structural application. To conduct this study, a nickel-based superalloy (Inconel 718) will be used as a model material because of its broad industrial applicability and its
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modality-specific embeddings, using physics-inspired data augmentations and mixture models (linear/quasi-linear behavior for XRF; non-linear Kubelka–Munk-inspired transformations for optical imaging
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their seniority, roles and preferential behaviour. The aim of the PhD is first to characterize the mechanisms that may be needed to model the dynamics a Wikipedia project, and define several levels of modelling
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
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and Research (MESR). Phd position The performance of recommendation algorithms that make use of human behavior heavily depends on their ability to capture the experience of people who interact with them
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behaviour. Lastly, we will develop methods for dynamically synthesizing and adapting control policies in real-time, based on human feedback, streaming observations, and evolving task goals. These adaptive