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, or electrophysiology recordings) identified in step 1.2. TheVirtualBrain framework [12] will assist in effectively managing the integration process. Aim 2: Model the computational de-association of memory traces 2.1
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computer science or a related field. General: Knowledge of hospital environments and the healthcare sector, as well as innovative technologies: AI algorithms, image and signal processing, segmentation, modeling
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master’s degree in mathematics, physics or informatics with a strong knowledge in machine learning. Skills: Coding in Python and/or R is required. Previous knowledge in archaeology and zoo-archaeology would
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neuroscience, biophysics, engineering, or related field. 2) Experience in one the following areas would be appreciated: in vivo electrophysiology, 2-photon imaging, optogenetics, microscopy. 3) Enthusiasm
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to muscle physiology and clinical applications. Specific Skills or Experience Required/Desirable: The project will involve experimental and computational work. The student will become familiar with a
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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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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