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computational reconstruction methods based on AI (deep learning) and/or compressed sensing. The envisioned imaging system will be based on a hybrid open-top light sheet microscope recently implemented in our lab
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Research Engineer/Postdoctoral Position Decision and Bayesian Computation (DBC) – Epiméthée (EPI) Laboratory Institut Pasteur, Paris | 25 rue du Docteur Roux, 75015 Paris Position Overview We
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Python-based frameworks or a web application) enabling image upload, AI-based analysis, and visualization of bacterial phenotypes. Perform image analysis using existing deep learning algorithms developed
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observed in Drosophila larvae. This interdisciplinary project combines biology, neuroscience, and computational modelling to understand how the larva’s body’s physical properties influence its motor control
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of the Department of Computational Biology and also holds a secondary affiliation with the Development Department, as well as an affiliation with CNRS. The recruited candidate will be affiliated 80
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significant computational component. We strongly recommend a background in machine learning and coding. Applicants with a background in areas such as computational neuroscience, reinforcement learning, or deep
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benjamin.devauchelle@pasteur.fr in Cc. The candidate should have a PhD in Human Genetics and the following skills: Strong interest in the field of genetics, neurobiology and psychiatry. Computer skills: strong level in
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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
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both spoken and written is required The candidat must have a Master (M2) of data science, computer science, applied mathematics The position is available starting from October. Salary according
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spoken and written is required The candidat must have a PhD in computer science, machine learning, or computational biology The position is available immediately and will remain open until filled