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in Artificial Intelligence (Machine Learning and Statistics) at CentraleSupélec, · Joël Eymery, Head of the Nanostructures and Synchrotron Radiation Team at CEA Grenoble, · Jean-Sébastien
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of remedial rules and institutions. Reframing remedies as an intermediary link between different systems crucial in the production of our imaginaries of justice, CURE aims to provide a new reading of labour law
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evidencing: (i) which scientific discoveries are more impactful than others; (ii) whether public attitudes to science change over time; (iii) how the public learn and talk about science; (iv) how different
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Postdoc in modelling Greenland and Himalaya precipitation using machine learning Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 26
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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assimilation and machine-learning techniques, (b) process understanding of the neighborhood risk of heat waves and fires associated with the change of weather pattern, and (c) novel algorithm development
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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Pneumatic Tires, Structure-Process-Properties Relationships. As part of it, we are currently looking for a postdoc on machine learning for road characterization. How will you contribute? Do you have proven
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of efficient and robust neural networks. About your role: Independent research in the area of mathematics of machine learning, focusing on the development as well as the analysis of different algorithms and
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of remedial rules and institutions. Reframing remedies as an intermediary link between different systems crucial in the production of our imaginaries of justice, CURE aims to provide a new reading of labour law