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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
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objective is to develop artificial intelligence methods that complement modeling techniques, particularly at the atomic scale, specific to the physical chemistry of materials. In this context
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atmospheric sciences and artificial intelligence (two PhD theses, one completed and one ongoing), and have already established a common framework ensuring effective collaboration. The appointed doctoral
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scienceYears of Research ExperienceNone Research FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria Knowledge of how generative artificial intelligence works Thesis in
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of electrical topologies (AC, DC, three-phase) and will integrate both standard and atypical wear cases. On this basis, high-performance artificial intelligence models will be developed. By combining neural
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, the environment and ecology, transportation, robotics, energy, culture, and artificial intelligence. Since the mid-2000s, significant research efforts have focused on textual entity linking, which involves
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of their life cycle. Recently, two technologies have emerged that offer new possibilities: high-throughput systems like flow chemistry, which can rapidly generate chemical data, and artificial intelligence (AI
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, engineering, bioinformatics, machine learning, artificial intelligence) to support minimally invasive and targeted preventive and predictive medicine capable of limiting age-related functional disorders
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protein sources, new ways to recycle carbon, nitrogen and phosphorus. Greenowl deploys theoretical tools, from the fields of automatic control and artificial intelligence and combines them with experimental