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learning, at the undergraduate, advanced and PhD levels. We regularly publish solid contributions at the best machine learning conferences. STIMA is characterized by a modern view of the statistical subject
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: Doctorat de l'Université Grenoble Alpes PHD Country: France Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/136951 Requirements Specific Requirements With a Master degree, or
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in solid mechanics framework Experience in non-linear solid material response and fracture modeling Experience in machine-learning modeling for solid mechanics applications Experience in
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year. You should have knowledge and experience in bridging quantum and classical machine learning, and be fluent in English, both written and spoken. Assesment criteria Qualifications that are considered
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
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both independently and as part of an international, interdisciplinary team Assets•Experience with computer vision or deep learning (e.g. PyTorch, TensorFlow)•Familiarity with street view imagery or other
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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analysis or habitat monitoring Highly valued: Experience applying AI or machine learning methods to remote sensing data Experience with drone-based point cloud collection Experience working with or advising
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to structured programming in C++ and Python - knowledge of linux / unix operating system - fluent knowledge of spoken and written English - fundamental knowlegde of machine learning (and statistics) - good level