66 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" positions at UNIVERSIDAD POLITECNICA DE MADRID
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the cloud-edge continuum for next-generation networks based on reinforcement learning. Evaluation of progress made in the project and design of a system for predictive behavior analysis, risk detection, and
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deep learning models to predict and analyze large-scale orbital capability. - Evaluate and optimize the performance of the models, comparing them with traditional orbital analysis methods. Where to apply
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integration of the project webpage into the institutional platform Uso de machine learning para estimar propiedades geomecánicas del terreno a partir de datos de laboratorio/ Use of machine learning to estimate
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contrato está financiado por el proyecto Hybrid Structures for Integration of Photovoltaic Cells in Car Bodies con referencia SYG-2024/ECO-1016 y acrónimo HyPVCAR-CM, dentro del Programa Ayudas a proyectos
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FieldEngineering » Industrial engineering Additional Information Eligibility criteria (https://www.upm.es/Investigacion/HRS4R/HRS4R/Seleccion ): COMENTARIOS ADICIONALES/ ADDITIONAL COMMENTS: Se aplican las pautas
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LanguagesENGLISHLevelGood Research FieldTechnology » Communication technology Additional Information Eligibility criteria (https://www.upm.es/Investigacion/HRS4R/HRS4R/Seleccion ): COMENTARIOS ADICIONALES/ADDITIONAL COMMENTS
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inteligencia artificial/machine learning. Tecnologías IoT y sistemas distribuidos. Conocimientos en FPGA. // Knowledge of artificial intelligence/machine learning, oT technologies and distributed systems, and
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deliverables writing, ability to work independently. Requisitos: Conocimientos de inteligencia artificial/machine learning. Diseño software, Gestión de datos, Arquitecturas backend (microservicios), Gestión de
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of water treatment processes and laboratory techniques; Ability to prepare technical reports and contribute to scientific writing. Computer Skills: Proficiency in Office/Google Workspace tools; asic data
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urban transformation. - Full day (37.5 hours), - Flexible check-in and check-out times Eligibility criteria Enviar CV a b.gatoo@upm.es Send CV to b.gatoo@upm.es (https://www.upm.es/Investigacion/HRS4R