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Description 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
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. Ideally, we would like to know the cochlear output precisely to study its effect on neural representations. However, because cochlear mechanics and neuronal processing are reciprocally coupled through
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equipped with evolving, plastic neural networks models, which process visual information and drive motor action. These virtual agents will navigate in virtual reconstructions of ants' natural environment, so
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computer vision. The dominant approach is based on deep neural networks applied to RGB images. These models have disadvantages such as: a) the need of large quantities of annotated data, which requires
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research & research methods Strong analytical skills and a collaborative mindset Experience with (Bayesian) statistics, deep neural network models, Kernel Methods, or data science Experience with neural data
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. The institute comprises 11 teams (120 staff including 48 researchers) and features state-of-the-art imaging, electrophysiology, and behavioral facilities. The "Neural Network Physiology" team studies information
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experience in at least one of the following topics: deep learning, reinforcement learning, probabilistic modeling, statistical learning, neural networks, or other related fields Interest in interdisciplinary
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/ or in vivo animal models of epilepsy - Sleep, circadian and / or stress neurophysiology - Immunostaining - Experience in behavioural tests - Modelling of neural network dynamics In
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team as part of a project aiming to demonstrate novel concepts of integrated modelocked or self pulsating semiconductor lasers. These miniaturized lasers meet the requirements of all-optical neural
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
national scientific initiatives. 1) Theoretical developments of control design methods applicable to periodic state systems 2) Application of artificial neural networks to the design of Leonov functions