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will focus on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural
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of Research Experience1 - 4 Additional Information Eligibility criteria - PhD in Phonetics/Phonology, Computational Linguistics, Automatic Speech Processing/Machine Learning or relevant related fields
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/CVF Conference on Computer Vision and Pattern Recognition. (2022). 3. Tancik, Matthew, et al. "Learned initializations for optimizing coordinate-based neural representations." Proceedings of the IEEE
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oscillation analyses • Practical Experience of deploying state-of-the-art machine learning techniques Desirable: • Ability to develop and apply new concepts • Verbal and written communication skills • Ability
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processing, involving machine learning techniques, as well as active participation in data collection from the detectors deployed on site. - Analysis of particle physics data applied to muography: filtering
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(Machine Learned Potentials) type approaches, and/or multi-objective approaches. - in-depth knowledge of Python programming languages (or C++, Fortran) and the Unix system; - Certified level in written and
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(segmentation analysis by machine learning) and automatic language processing on large quantities of digitised historical photographs and their metadata. - management, enrichment and structuring of project data
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and machine learning Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8254-SYLDES-005/Default.aspx Work Location(s) Number of offers available1Company/InstituteLaboratoire
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machine-learning is required, as well as a good knowledge of associated theoretical tools (statistical physics of liquids, ...; programming experience among: Python, Fortran, C, C++, ...). A good command of
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simulation and/or machine-learning is required, as well as a good knowledge of associated theoretical tools (statistical physics of liquids, ...; programming experience among: Python, Fortran, C, C++, ...). A