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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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/chercheur-fh-en-simulation-des-deformations-des-tis… Requirements Research FieldEngineering » Computer engineeringEducation LevelPhD or equivalent Research FieldBiological sciences » Biological
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difficult to couple with basin simulators. Geochemical metamodels, particularly those based on machine learning, can significantly reduce computation times while maintaining physico-chemical consistency
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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria The position requires a PhD in machine learning, NLP, causality, or a related discipline, with a strong command of deep
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or equivalent Skills/Qualifications - PhD in bioinformatics or related subjects - Expertise in python coding - Experience and good understanding of neural networks and machine learning - Fluent written and spoken
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 24 days ago
disseminate the developed methods. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2025-09574 Requirements Skills/Qualifications PhD in Computer Science, Machine Learning, Bioinformatics
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Requirements Research FieldComputer science » Computer systemsEducation LevelPhD or equivalent Skills/Qualifications Knowledge • Solid understanding of machine learning, deep learning, and modern AI techniques
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
Qualifications PhD in machine learning, computer vision or a related field. Established expertise in deep learning methods applied to images analysis. Experiences with generative models, volumetric image
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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conceptual DFT (linear response function, Fukui functions) or QTAIM theory (delocalization index), and their validation on a set of compounds known from the literature - interfacing a MLIP (Machine-Learned