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, statistics and scientific computing. * Proficiency in a scientific programming language, particularly Python, and the ability to develop reproducible processing procedures. * Knowledge of machine learning and
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the functional links between transcription factor condensate formation and autophagy, and the involvement of these processes in the temporal interpretation of auxin information and the control of organogenesis
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- Study of stability under operation - Development of kinetic models - Reactor modeling The work will be carried out at the ICPEES (Institut de chimie et Procéder pour l'Energie, l'Environnement et la Santé
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changeYears of Research ExperienceNone Additional Information Eligibility criteria - PhD in atmospheric physics with a speciality in cloud, radiative and convective processes - Some experience with conceptual
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to best practices: ethics, animal experimentation regulations, and current standards. -Data processing and analysis:Cleaning, structuring, and annotating datasets for optimal use. Analyzing raw results and
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physics and quantum chromodynamics. Knowledge of computer programming is a plus. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR3681-CAMFLO-002/Default.aspx Work Location(s) Number
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to artifacts such as non specific absorption, parasitic reactions, or diffusion based resolution loss. In this project, we will design and control a surface modifcaiton process based on a double, photo
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for the heliophysics component, and LISN in Orsay for the computer science and natural language processing component. Status meetings every two weeks, alternately at LIRA in Meudon and at LISN in Orsay. The PhD thesis
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exhibit novel nonlinear behaviors, opening the way to the experimental observation of fundamental processes that have so far remained largely unexplored. Among the various approaches proposed to reach this
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bachelor's students and ensuring the proper maintenance and operation of the synthesis lab in accordance with the recommendations provided by funding agencies and the laboratory administration. • Develop