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conducting experiments for training and evaluating deep neural networks Knowledge of multi-modal learning, transfer learning, transformers, or self-supervised learning Experience in dealing with large medical
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Convolucionales / - Mastery of Convolutional Neural Networks - Procesamiento de imágenes de MRI /MRI image processing - Conversión de formato DICOM a NIfTI / DICOM to NIfTI format conversion
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image processing, classification, multi-temporal analysis, and data fusion, using advanced automatic analysis methods such as deep neural networks and artificial intelligence is essential. Specific
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Inria, the French national research institute for the digital sciences | Bron, Rhone Alpes | France | about 1 month ago
the principals of open-science. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2025-09545 Requirements Skills/Qualifications Strong background in recurrent neural networks (rate‑based
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: Developing state-of-the-art neural networks to accelerate the development of formulations in the pharmaceutical sector. Collaborating on the implementation of these techniques within a company. Contributing to
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architectures in domains such as generative AI, large language models, neural networks, and imaging as well as to integrate various types of data to advance research and improve clinical decision making. As a
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National University of Science and Technology POLITEHNICA Bucharest, Pitesti Branch | Romania | 24 days ago
artificial intelligence algorithms, including machine learning methods, deep neural networks, and adaptive algorithms for optimizing the behavior of dynamic systems is required. The candidate must master the
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radar image processing, classification, multi-temporal analysis, and data fusion, using advanced automatic analysis methods such as deep neural networks and artificial intelligence is essential. Specific
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related field by the beginning of the thesis (~ September 2026). - Good understanding of networks, protocols, etc. - Good understanding of artificial intelligence (regression models, neural networks, etc
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for Smart Economy 2021–2027 (FENG). Neural Radiance Fields (NeRFs) have demonstrated the remarkable potential of neural networks to capture the intricacies of 3D objects. By encoding the shape and color