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Field
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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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València announcing a selection process for an indefinite employment contract within the framework of a Line of Research R&D+i Line: High-performance algorithms for vector processors https://www.upv.es
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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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of federated algorithms that enable fair management of the advantages and duties of energy communities in which vulnerable people live. The automatic generation of data models using AI technology will enable
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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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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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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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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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implementation of security provisioning algorithm in DFL environment Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research FieldEngineering » Communication