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in medical image analysis. The ideal profile should demonstrate experience in developing deep learning algorithms applied to radiological imaging, particularly in breast and thoracic domains. Knowledge
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with peer review system. Expertise in optimization software and algorithms as well as in Reliability Analysis (maximum 20 points). • Projects and academic/research works: 5 points/item • Author or co
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apply machine learning algorithms with special attention to digital footprint reduction and data privacy. Functions to be developed: Develop methodologies and experiments to measure and optimize
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and Prisma stack. Help integrate the application with the Jutge.org public API to synchronize data. Collaborate in the implementation of algorithms for the automatic evaluation of the difficulty
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algorithms and investigate protests linked to the environmental impact of artificial intelligence and data centres. Contribute to the academic and artistic production of the project by writing articles
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for developing AI algorithms: NumPy, Pandas, Matplotlib, PyTorch. Development and implementation of machine learning and AI algorithms based on neural networks and deep learning. 3.3. Additional education (maximum
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laboratory automation. Experience in laboratory process automation, algorithm development and machine learning and artificial intelligence (AI) applications. Experience in laboratories with quality management
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Infrastructure? No Offer Description Mission: Research and develop robotic perception algorithms that allow obtaining a 3D representation of complex environments; monitoring and presentation of results. Functions
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Offer Description The researcher will develop various applications, algorithms, and AI techniques for Virtual Power Plants (VPPs) within the distribution grid environment. These will include neural
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estadísticos para su integración en plataformas de datos. --------------------------- Design and development of statistical data analysis algorithms for integration into data platforms. Where to apply E-mail