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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome
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postdoctoral fellowship at ENS Lyon in the field of machine learning. The position is part of the research project "Neural networks for homomorphic encryption", funded by Inria. Fully homomorphic encryption (FHE
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research centre dedicated to understanding normal and pathological brain function and developing new diagnostic and therapeutic approaches. Website: https://neurosciences.univ-grenoble-alpes.fr You will be
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of the project is to design, model and simulate neural networks based on magnetic skyrmion nucleation and propagation. The second objective is to fabricate these hardware neural networks, characterize
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The postdoctoral researcher will join the "Network Dynamics & Computations" team led by Srdjan Ostojic and develop research projects on modeling neural circuits and their role in behavior. The work will focus
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) methods. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5253-MOUBEN-002/Candidater.aspx Requirements Research FieldChemistryEducation LevelPhD or equivalent Research FieldChemistryEducation
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sustainability issues. In particular, the “Probability/Optimization” group focuses on the theoretical understanding of algorithms used in machine learning, for training large neural networks and tuning
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validated at CPPM. In parallel, the candidate will improve data reconstruction algorithms by using artificial intelligence techniques (e.g. neural networks), to optimize the separation between signal and
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FieldComputer scienceYears of Research Experience1 - 4 Research FieldMathematicsYears of Research Experience1 - 4 Additional Information Eligibility criteria Skills/knowledge: computer vision, neural networks
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
/logical rules with neural networks to increase accuracy and explainability. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-09730 Requirements Skills/Qualifications PhD in neuro