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information * Applied mathematics, computational physics, or computer science - Strong programming skills (e.g., Python, PyTorch, TensorFlow) - Experience in one or more of the following areas: * Generative AI
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Technical skills : - Ability to handle large datasets (hundred thousands to millions of rows) using a programming language (e.g. R, Python, MATLAB) - Good knowledge of descriptive multivariate data analyses
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to continuously learn new skills, methods and concepts, and 2) to enjoy finding new solutions in the face of new and unforeseen difficulties. The ideal candidate has very good 1) python programming skills, 2
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. • PIC simulation codes. • Data analysis using C++/ROOT and/or Python. • Detector simulation using GEANT4. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7638-ARNSPE-001
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in Python, PyTorch/TensorFlow, and medical visualization tools (e.g., 3D Slicer, ITK-SNAP, MONAI...). - Mastery of deep learning platforms Tensorflow/Pytorch/scikitlearn - English: high level Website
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algorithm development and satellite remote sensing • Good written and spoken English • Ability to work independently as well as in a team • Proficiency in programming languages (e.g. Python, R, Fortran
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independently as well as in a team • Proficiency in programming languages (e.g. Python, R, Fortran) Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8518-MARLIE-021/Default.aspx Work
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of Research ExperienceNone Additional Information Eligibility criteria Knowledge in steganography, steganalysis, and generated image detection. Knowledge in image generation. Proficiency in Python. Additional
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programming in Python and MATLAB; version control (git) and reproducible workflows. * Experience with MEG/EEG analysis; familiarity with MNE-Python/SPM/FieldTrip; comfort with source reconstruction and signal
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ExperienceNone Additional Information Eligibility criteria Python programming. Analysis and development of ML and DL models using standard data science libraries. Data engineering from molecular dynamics