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Field
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máquina/profundo y segmentación aplicado al procesamiento de imágenes y vídeo / - Development of embedded systems for machine/deep learning and segmentation applied to image and video processing
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internal reports and manuscripts. Requirements: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related. Solid knowledge of machine learning, including graph neural
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, required to adequately incorporate molecular data, and model regulations of inflammatory and degenerative processes. Available datasets at the molecular level will be incorporated through machine learning
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systems for artificial intelligence and machine learning. - Programming very low power consumption embedded systems. - Cloud and edge computing. - Development of embedded systems for the Internet of Things
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Skills/Qualifications Additional undergraduate degrees related to mathematics, physics, computer science, telecommunications, or engineering. Knowledge of machine learning, mathematics, and probability and
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: Apply "machine learning" techniques. Perform statistical analysis of clinical data of critically ill patients. Validate the model with experimental data. Support in the preparation of reports and
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development of prompt engineering, machine learning, and NLP techniques to process data and build this model, adding feedback based on the results. The selected candidate must live in Madrid during the period
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recruiting excellent candidates in the areas of Machine Learning, including Formal Reasoning About ML Systems, Explainable AI, Data Analysis at Large Scale, etc.; Privacy; Quantum Computing; Software
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5 Sep 2025 Job Information Organisation/Company UNIVERSIDAD POLITECNICA DE MADRID Department HRS4R Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1
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experience, adequacy to the proposed profile (0-50 points): Strong background in wireless communications, mathematics, and machine learning, programming skills. Other merits (0-20 points): Fluent oral and