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on the ERC-funded project ‘Understanding the Consequences of Major Health Crises for Education: Learning from the COVID-19 Pandemic (LEARN)’. The LEARN project: Health crises, natural disasters, and violent
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). - Familiarity with machine learning principles and generative/classification models (PyTorch Lightning, torch, scikit-learn, etc.), as well as data/model analysis methods (PCA, t-SNE, etc.). - Proficiency in
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existing structural and functional MRI data, acquire new data in collaboration with clinical researchers, and prepare publications and conference presentations. - Study preparation - Data acquisition (MRI
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the project team, you will ensure the simulation of drone missions using state-of-the-art tools for AI learning and demonstration. You will be responsible for producing training data for vision models and
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Description CNRS offers a 18-month fixed-term contract researcher position to work on the recently funded project ACCTS (“Assessing cirrus cloud thinning strategies by learning from aerosol-cirrus interactions
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); writing skills in French and English Appreciated: - Interest in the economics of innovation and regional development; - Project management; - Creativity, self-learning ability, ability to make proposals
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notebook - Present the results of syntheses and characterisations, ensuring their follow-up and quality - Master basic IT tools, ability to learn new ones - Work with rigour, reliability and initiative
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. This is optional and can be tailored to the postdoc’s interests and career goals. The net monthly salary is €2,380 The contract duration is 18 months Where to apply E-mail aline.muyle@cnrs.fr Requirements
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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elucidating the molecular and cellular mechanisms of the late phase of long-term potentiation (LTP), a key process in learning and memory. The project is based on the development and use of an innovative