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- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
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Field
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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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) and satellite platforms, and surface energy balance models will be used to obtain evapotranspiration (ET); computer vision and machine learning techniques will also be used to identify and count fruits
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Engineering). - Theoretical foundations of 6G RAN and autonomous systems o Proven knowledge of AI-native RAN systems. Indicative skills/experience: - Deep understanding of 5G/6G RAN architecture (O-RAN, NG-RAN
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of machine-learning models at catchment to regional scales. LanguagesENGLISHLevelExcellent Additional Information Work Location(s) Number of offers available2Company/InstituteUniversitat Politècnica de
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biology and bioinformatics, as well as in Machine Learning (including Large Language Models). Good understanding of evolutionary and molecular biology concepts, and good statistical (data analysis) and
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for data augmentation, small language models, anomaly detection using learning methods, and explainability techniques for decision-making. The research will involve designing and developing prototypes
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structural bioinformatics, machine learning, and high-performance computing, we will build the first Human Proteome-Wide Frustration Atlas — a resource to better classify genetic Single Nucleotide Variants
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or equivalent Skills/Qualifications Valued/Preferred qualifications: Experience in software solution development Experience with machine learning models Experience in R&D&I projects (Research, Development and
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on the application of machine learning in satellite communications (20 points). Participation in European Space Agency projects (20 points). Other skills that are valuable, but not mandatory are: Knowledge of over
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the development of components using agent-based modeling techniques, reinforcement learning, and other explainable artificial intelligence modules for decision-making, situation assessment, and operational support