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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 1 day ago
of the scale in force. We are seeking a Machine Learning Engineer to design and develop a Python software library for evaluating theoretical generalization bounds in deep learning. The objective is to bridge
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research in the areas of safety-critical control theory and machine learning. The role will focus on combining new theory or method in nonlinear system control and state-of-the-art machine learning systems
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models using general-purpose foundational models. Use of deep learning libraries: PyTorch. Experience publishing scientific papers at prestigious conferences on machine learning and AI. Other criteria 30
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models using general-purpose foundational models. Use of deep learning libraries: PyTorch. Experience publishing scientific papers at prestigious conferences on machine learning and AI. Other criteria 20
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practice of machine learning would be an asset. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8188-MARHEC-007/Default.aspx Work Location(s) Number of offers available2Company
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Robot Learning (https://ellis-stuttgart.eu/research/ ). To strengthen our joint research activities, we are looking for an excellent and highly motivated scientist with an outstanding early-career track
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About Us Georgia Southern University is the state's largest and most comprehensive center of higher learning south of Atlanta, and one of the most dynamic public universities in the Southeast
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research in the areas of safety-critical control theory and machine learning. The role will focus on combining new theory or method in nonlinear system control and state-of-the-art machine learning systems
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mechanics, information theory, stochastic processes, population dynamics, and neural networks. Within this framework, machine learning systems and artificial generative models will also be considered, where
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learning. We are looking for a strong, independent computational researcher who wants to develop original machine learning methods, shape their research direction, and collaborate closely with clinicians