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between machine learning and robotics. The first part of the project will involve working with members of various CNRS laboratories to map the main open-source tools made available to the community by
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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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strong background in Artificial Intelligence (AI) methods, including machine learning, and data science methods as a whole. Experience with Python programming language and classical AI libraries is
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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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of the Ministry of Higher Education and Research (MESR). The project focuses on the development of cutting-edge machine learning methods aimed at predicting atomistic structures (i.e., the arrangement of atoms
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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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(which is often easier to create particularly in for multilingual processing typically by using machine translation) and further improving the model using preference data. Preference learning has gained
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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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the suited security micro-services. This automation is made possible by formalizing micro-services-based applications and their data-flows, and machine learning techniques for selecting the micro-services
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, where innovative ideas and scientific advances are encouraged and valued. Federated learning (FL) is a promising paradigm that is gaining grip in the context of privacy-preserving machine learning