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Field
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Job related to staff position within a Research Infrastructure? No Offer Description Mission: Cooperate in the development of an educational application with models and techniques for massive data
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Description Implement and validate machine learning models and statistical algorithms for data imputation, anomaly detection and uncertainty management in geospatial environments. Collaborate in the preparation
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) Interpretable machine learning for network adaptation. In this thesis, the student will study how interpretable models and explainable learning algorithms could be used in real cellular networks for safe
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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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, among several others. Some examples are provided next: a) Structural analysis, uncertainty quantification and optimization. b) In house software development required to achieve the objectives
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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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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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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 20 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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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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implementation of security provisioning algorithm in DFL environment Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research FieldEngineering » Communication