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of a multi-modal dataset.; - Implementation of a software module for storing datasets according to a pre-defined standard.; - Development of routines for testing existing ML algorithms on a multimodal
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acceptance by technology takers and final users.; ; The main objectives of the Fellowship are:; 1) Apply data analysis and identify energy management use cases in renewable energy communities and industry.; 2
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, algorithms 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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experience in programming with R and RStudio.; Knowledge of Data Visualisation and Multivariate Analysis.; Minimum requirements: Enrolled in a Master’s program in the relevant admission area. Knowledge
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engagement with suppliers for comparative analysis of commercial solutions.; • Participation in the installation and integration of the characterization system within the laboratory environment.; • Execution
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of these features in other DevOps platforms, such as GitLab. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Experimental analysis of the requirements, functionalities, and limitations of the GitHub Actions
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fellows, including writing scientific articles and participating in collaborative projects. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - Survey and critical analysis of the state-of-the-art
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: The AI-RBD (AI-driven video analysis for REM behavior disorder detection
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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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-world environments; - Data analysis and correlation; - Management of the code repository and the collected database; - Participation in project meetings; - Writing scientific articles. 3. BRIEF