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four years, in the cases of students enrolled in a PhD. Scientific advisor: Alípio Jorge Workplace: INESC TEC, Porto, Portugal Maintenance stipend: 1309.64, according to the table of monthly maintenance
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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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the usability and user experience of the solutions - Prepare activity reports and scientific articles 4. REQUIRED PROFILE: Admission requirements: PhD student, with a completed master's degree The awarding
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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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awarded to students who are enrolled in non-award courses, or up to four years, in the cases of students enrolled in a PhD. Scientific advisor: João Tiago Paulo Workplace: INESC TEC, Braga, Portugal