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Master/engineer degree in computer science, applied mathematics, data science with background in image processing, imaging inverse problems, deep learning and optimisation. Good coding skills for numerical
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, but are not limited to, neural coding in the visual cortex, multimodal information processing, state-dependent processing, visual perception, development of imaging tools for in vivo neuronal recordings
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a challenging problem. Candidate profile PhD on optimization and/or image processing. Strong background in applied mathematics, image processing, learning methods and algorithms. Good coding skills
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to analysis by magnetic microscopy. To achieve this, it is necessary to bring together, make compatible and carry out the calibration between different existing codes that are used during the key stages
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done using semiconducting materials, with transistors performing logical operations (“NOT”, “AND” etc.). A new paradigm proposes to use magnetic materials to perform these operations, by en-coding
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rodent studies—obtained by electrophysiology, fiber photometry, and calcium imaging in vivo recordings—the project will build a biologically grounded SNN model of memory de-association. The ultimate goal
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mechanoelectrical feedback, it requires specific tools to uncouple them and to decode the transformation of complex acoustic stimuli by the brain. In the lab, we are developing electrophysiological and imaging
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deal with numerical and/or categorical data [e.g. Klassen et al., 2018], textual data [e.g Assael et al., 2022], images [e.g. Horache et al., 2021 and geospatial data [Ramazzotti, 2020]. Applications
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more (for an overview of these technologies, see http://behaverse.org/ ). Your role in this team will be to develop computational models and data analysis code to process large, multimodal behavioral
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number of techniques routinely used in the lab including histology, confocal microscopy and image processing. Prior expertise in cell culture, image analysis and coding would be highly appreciated. Part of