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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 17 days ago
agroecological recommendations through cutting-edge Machine Learning techniques. LanguagesFRENCHLevelBasic LanguagesENGLISHLevelGood Additional Information Benefits Subsidized meals Partial reimbursement of public
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of research and education, covering all aspects of computer science, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking
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well as an active engagement in the 3RTG activities. Requirements: successfully completed university degree (Master's, Diploma or equivalent) and relevant PhD in Computer Science, Computer Engineering, or related
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL, you will collaborate with a dynamic team of scientists and
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imagery). Experience in building data models using Python or other statistical and/or mathematical programming packages. Proficiency in developing machine learning algorithms to analyze spatial-temporal
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. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, quantum conputing
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resonance spectroscopy, imaging (MRI), Applied Mathematics or Machine learning. We are looking for talented, highly-motivated experimentally skilled young scientists with Master degrees or equivalent or PhD
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. Preferred Qualifications • Experience with deep learning architectures applied to geophysical or environmental data. • Familiarity with physics-informed machine learning or hybrid modeling approaches
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that promote inclusivity, fairness, and productive discourse online. We seek a candidate with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running