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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
ablation and deep brain stimulation options for pediatric patients. Special Physical/Mental Requirements Campus Security Authority Responsibilities Not Applicable. Special Instructions Quick Link https
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solutions that enhance ecological monitoring, improve resilience planning, and promote sustainable resource management. Development of a Detection Transformer through Attentive Deep Learning and Explainable
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individuals and patients. These projects involve large-scale neuroimaging data collection at 3T and 7T, computational modeling of brain responses using machine learning methods, and cross-institutional clinical
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include the development of finite elements methods, as well as inverse design strategies based on deep-learning and Neural Networks approaches. The latter will then bring the project to the experimental
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automated configuration mechanisms based on fingerprinting and machine learning to ensure traffic analysis remains faithful to the behavior of the monitored machines. Finally, you will validate your solutions
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team players and passionate on cutting edge computer vision and machine learning technologies, as well as possess deep understanding of machine learning technology and experience on turning machine
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Skills :Programming, Research Knowledge :IA, Deep Learning, Python Where to apply Website https://rubis.univ-spn.fr/offres/voir/206 Requirements Specific Requirements Be a graduate of an Engineering
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family's wellbeing and allows you to be a part of the life of a vibrant and active college campus. To learn more, go to Baylor Benefits & Advantages. Explore & Engage Learn more about Baylor and our
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applications for faculty positions in Computer Science. Faculty specialising in data science, machine learning (deep learning, reinforcement learning, multimodal learning), Generative AI, and computer graphics
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools