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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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optimization. At the same time, AI models, especially deep neural networks, are becoming increasingly complex, with energy consumption and carbon footprint emerging as major concerns. For instance, training a
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implement and train neural network architectures, including Physics-Informed Neural Networks (PINNs), in order to integrate physical constraints into the learning process and improve the identification and
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Description The overall objective is to improve the integration of polar ice sheets into Earth system models by using neural network emulators at the interface between an Antarctic ice sheet model (Elmer/Ice
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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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have become a major challenge for understanding, recording, and modulating neuronal network activity, ranging from in vitro cellular models to implantable neurotechnological applications. In the long
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perturbations on neural coding and behavior. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR8003-DESFRI-005/Default.aspx Requirements Research FieldNeurosciencesEducation LevelMaster Degree
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photonic systems, in particular, make it possible to harness the richness of optical dynamics to perform complex operations inspired by biological neural networks. However, current approaches face
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of current systems. Considering this, memristors are innovative electronic components that enable the creation of hardware neural networks inspired by the brain, potentially reducing the energy consumption
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. The work will be primarily computational, focusing on the development of deep neural network model architectures and their training. It will involve extending the preliminary results we have already obtained