10 machine-learning "https:" "https:" "https:" positions at UNIVERSIDAD POLITECNICA DE MADRID in Spain
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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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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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of machine learning tools in the process industry - General research tasks (scientific article writing, oral presentation of results, document management, etc.) - Technoeconomic analysis and life cycle
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básicos de Machine Learning. // Basic knowledge of Machine Learning. • Habilidades en Ingeniería de Redes y Computación en la Nube-Edge. // Knowledge of Network Ingenieering and Cloud – Edge computing
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or equivalent Skills/Qualifications A Bachelor's Degree or an equivalent in Computer Science, Telecommunication Engineering, or a related field with a strong academic background in Machine learning, Natural
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campos de interés. Basic qualifications: Master's degree in Electrical/Electronic/Computer/Telecommunications Engineering, Computer Science, Physics, or a related field. Outstanding undergraduate students
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architectures based on MLIR / LLVM. - Research on optimization techniques for extracting and mapping data flow graphs on custom archtectures. - Research on custom dialects on MLIR. Where to apply E-mail
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), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas, SHAP, TensorFlow, etc.) y específicas de análisis de imágenes, estadística, simulación, entornos cloud (tipo Kubernetes