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, statistics and probabilities • data science, machine learning, artificial intelligence • optimisation • power system management, integration of renewables • energy forecasting Expected level in french : bon
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. The team is associated with the Institut Pasteur's Computational Biology Department, UMR3738 and the PRAIRIE Artificial Intelligence Institute. The team recently won ERC StG funding, which is the subject of
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high-quality research in one of the Department's key research areas: (i) Artificial Intelligence and Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition
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interdisciplinary programmes in key strategic areas including precision oncology, advanced materials, regional oceanography, artificial intelligence and robotics, data science, cognitive and brain science and
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training and research around the development and delivery of digital health and care interventions, digital research methodology and ‘big data’ analysis Research could include the use of Artificial
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in data and computational science, including omics and artificial intelligence approaches are of particular interest, but strong candidates in any cancer-related biomedical area are encouraged to apply
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the existential challenge to the humankind: excessive energy consumption by data-intensive technologies such as Artificial Intelligence, Internet of Things and cloud computing. Successful candidates will hold a PhD
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artificial intelligence/machine learning may be applied are encouraged to apply. If you are interested in research in brain-machine interfaces, and are unsure about whether you have the right background
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applied applied artificial intelligence for industry applications as well as publications in top-tier international conferences and journals, as well as real-world implementations. If interested, please
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, Computational Physics, Bioinformatics, Artificial Intelligence or similar. Proven knowledge of scientific English (minimum level B2). Experience in scientific programming (Python, Julia, Matlab or similar