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algorithms to combine information on cardiovascular activity obtained from heart sound signals, electrocardiogram, and photoplethysmography. Investigate the inclusion of prior knowledge about the application
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insurance, supported by INESC TEC. 2. OBJECTIVES: Over the years, large-scale infrastructures have been developed to support high computing performance without worrying about energy consumption. With
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neural networks, enabling us to estimate the reliability of a single decision of this algorithm. Regarding generalisation, recent self-supervised learning paradigms have strong synergies with the multi
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factors: - Experience in designing and implementing key-value stores; - Solid knowledge on order and durability guarantees for efficient logging systems.; Minimum requirements: - Solid knowledge
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the AC average will be considered excluded on absolute merit. The top five candidates approved on absolute merit will be qualified for the individual interview. The Final Grade (CF) is obtained by
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. The top five candidates approved on absolute merit will be qualified for the individual interview. The Final Grade (CF) is obtained by the weighted average of AC (70) and EI (30). DISABILITY INCENTIVE
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experience, basic knowledge of dynamic/control systems, undergraduate grade greater than or equal to 13 (scale from 0 to 20). 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and
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on absolute merit. The top five candidates approved on absolute merit will be qualified for the individual interview. The Final Grade (CF) is obtained by the weighted average of AC (70) and EI (30). DISABILITY
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will be qualified for the individual interview. The Final Grade (CF) is obtained by the weighted average of AC (80) and EI (20). DISABILITY INCENTIVE Candidates who present a degree of disability equal
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will be qualified for the individual interview. The Final Grade (CF) is obtained by the weighted average of AC (60) and EI (40). DISABILITY INCENTIVE Candidates who present a degree of disability equal