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Field
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of fully autonomous navigation systems. Main responsibilities Develop and optimize autonomous navigation algorithms for outdoor mobile robots. Integrate and fuse data from perceptual sensors (LiDAR, RGB
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of Artificial Intelligence in Green Algorithms Research line / Scientific-technical services: Development of algorithms that are energy efficient Grant/funding period: START: 01/05/2024 END: 31/03/2027 Centre
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----------------- - Development of automatic classification algorithms. - Data quality analysis. - Development of Fourier and wavelet analysis algorithms for time series analysis. Where to apply E-mail juancarlos.losada@upm.es
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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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include the development and implementation of control algorithms on FPGA platforms, experimental testing using Hardware-in-the-Loop (HIL) setups, data analysis, and preparation of scientific publications
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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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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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) 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 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