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SCIENCE Scientific subarea: Computer Systems Grant duration: 6 months, starting on 2025-04-01 , with the possibility of being renewed until the end of the project. Scientific advisor: Miguel Coimbra Workplace: INESC
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resources, and reduce operational costs. In this context, the following objectives are proposed:; - Development of a methodology for the optimal sizing of the main components of a green Power-to-Hydrogen (P2H
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of Higher Education Institutions. Preference factors: Frequency of a master in data analytics. Minimum requirements: Python knowledge. Experience of developing software for network science. 5. EVALUATION
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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 candidates will be involved in the development of interface
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appropriate methods for the study in question; - develop the research capacity through the application of the selected methods; - exercise a critical spirit in the evaluation of the research process and the
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the knowledge of the state of the art in deep learning for human pose detection; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
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PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning for lung cancer imaging data; - identify and select the appropriate methods for the study in question; - develop
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; - develop the research capacity through the application of the selected methods; - exercise a critical spirit in the evaluation of the research process and the results obtained.; 4. REQUIRED PROFILE
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: COMPUTER SCIENCE Scientific subarea: Digital systems,Informatics Grant duration: 6 months, starting on 2025-04-01 , with the possibility of being renewed until the end of the project. Scientific advisor
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include the list of previous fellowships, their type, beginning and end dates, funding entities and host institutions); 3. Certificate or diploma degree; 4. Proof of enrollment in a degree awarding study