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: - Experience in ML and frameworks for ML; Experience on Multimedia analysis; proficiency in english 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first
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high-performance computing environments, including scripting, experimental evaluations, collection and analysis of performance, resource usage, and energy consumption metrics. 5. EVALUATION
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for parameterisation and scenario analysis; - Development of dashboards for monitoring performance indicators.; Phase 2 - Application of Parameter Calculation Support ; - Development of computational modules
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TEC. 2. OBJECTIVES: Collaborate with clinical partners in data collection and annotation Design and implement new deep learning solutions for the analysis of heart sound auscultation, electrocardiogram
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these systems improve the performance of physicians, they are limiting themselves to a subjective and qualitative analysis. The objective of this project is to improve interactive systems for medical use. 3
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to variable external loads:; i. Analysis and modeling of the robotic manipulator and the devices to be integrated (end-effector), defining the relevant mechanical and control parameters.; ii. Development
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-of-the-art deep neural networks for musical audio, with special focus on timbre analysis and manipulation.; - Identify and implement approaches for explainable ML models.; - Cooperate in writing scientific
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: • Specification and design of an antenna characterization system, focusing on technical and functional requirements.; • Market research and engagement with suppliers for comparative analysis of commercial solutions
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with a focus on traditional machine learning (shallow learning) and deep learning methodologies. Knowledge of Data Science, including the development of data analysis and visualisation pipelines. 5
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DevOps contexts. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Study of security vulnerabilities associated with GitHub Actions and of state-of-the-art tools for their dynamic analysis