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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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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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: 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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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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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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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 | 20 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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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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. Tissue engineering and regenerative medicine: integration of biomechanical principles into the design of scaffolds, organoids, and artificial tissues. Mechanics of cardiovascular and neural tissues
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. Investigate and implement optimum sampling strategies, including sparse and compressed sampling techniques. Explore the applicability of neural networks in clinical workflows, ensuring solutions are practical