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- University of A Coruña
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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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title: UDC-Inditex Chair of Artificial Intelligence in Green Algorithms Research line / Scientific-technical services: Development of algorithms that are energy efficient Grant/funding period: START: 01
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title: UDC-Inditex Chair of Artificial Intelligence in Green Algorithms Research line / Scientific-technical services: Development of algorithms that are energy efficient Grant/funding period: START: 01
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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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implementation of security provisioning algorithm in DFL environment Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research FieldEngineering » Communication
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III of the Call for Proposals - Demonstrable experience in tasks related to multibody systems dynamics, particularly slack modelling and data fusion algorithms with computational models. - Candidates
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III of the Call for Proposals. - Demonstrable experience in tasks related to multibody systems dynamics, particularly slack modeling and data fusion algorithms with computational models. - Candidates
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Analytics research group at the Catalonia Institute for Energy Research (IREC) is looking for a senior researcher (R2) to join our team and contribute to the development and integration of advanced algorithms
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, CU/DU/RU split). - AI/ML algorithms and methods for joint compute and radio resource management at the 6G edge leveraging accelerators - Control- and data-plane separation, real-time scheduling, and
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algorithms to extract clinical indices and provide new digital biomarkers for sleep medicine. The aim of the project is to develop new algorithms and tools of Digital Health for non-invasive, home-based sleep