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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
, reference no. 2023.18249.ICDT, financed by national funds through FCT/MCTES (PIDDAC Workplan: Development of methodologies and machine learning algorithms for the detection of anomalous behaviors in flow rate
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a master's degree in Computer Science or related fields1; Be a student enrolled in a doctoral program in Computer Engineering or Computer Science or in an advanced training course - a requirement to
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of Computer Science and Electrical and Computer Engineering. INESC-ID’s research impact is focused on four Thematic Lines Energy transition Life and health technology Security and privacy. Societal digital
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Wrocław University of Science and Technology / Faculty of Information and Telecommunication Technology | Poland | 2 months ago
creating a semantic repository for storing and indexing tax documents, designing machine learning algorithms to represent data in embedding spaces, and building tools for semantic search, interpretation
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supported by own funds of the Faculty of Engineering of the University of Porto, , under the following conditions: Scientific Area: Reinforcement Learning, Machine Learning Admission requirements: Candidates
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, Economics, Management, or related fields. [1] ; Be a student enrolled in a doctoral program in Computer Engineering or Computer Science - a requirement to be duly proven at the time of hiring. 2; 3. Preferred
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machine-learning methods for sample segmentation and classification. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: The fellow will join the INESC TEC team within the LIBScan project, carrying
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Escola Superior de Design, Gestão e Tecnologias da Produção de Aveiro - Norte da Universidade de Aveiro | Portugal | 2 months ago
Produção de Aveiro - Norte (ESAN-UA), under the following conditions: 1. Scientific Area: Electronic and computer engineering, computer and information sciences, mechanical engineering or related areas. 2
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experience in the use of machine learning algorithms applied to engineering phenomena, especially in the areas of structural engineering; Have applied knowledge in the finite element method; Have proven
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using machine learning; Interpretation of soil profiles and moisture maps. Development and validation of digital tools: Support in building georeferenced web interfaces for data visualization