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- Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID
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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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for applications for one research grant within the framework of project ISA4RL - Integrating Instance Space Analysis with Auto-Reinforcement Learning for Adaptive Algorithm Selection and Configuration
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-vision algorithms with edge-computing processing for the automatic detection of non-conformities. Machine-learning techniques will be applied to optimize cutting parameters, and the module will be
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 13 days 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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Escola Superior de Design, Gestão e Tecnologias da Produção de Aveiro - Norte da Universidade de Aveiro | Portugal | 26 days ago
Regulations of the University of Aveiro. 5. Work Plan: This project aims to develop solutions based on Artificial Intelligence for optimizing additive manufacturing processes. Machine learning techniques will
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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
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
skills. Have very good knowledge of machine-learning and data science methods, especially for timeseries data Have very good programming skills in programming languages such as Python. Have previous
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of Artificial Intelligence and experience using machine learning and deep learning development environments and libraries is a plus. As set forth FCT Research Scholarship Regulation No. 950/2019 of December 16
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that do not confer an academic degree, in the area or area related to that requested in the tender. Preferential factors: Have demonstrable experience in the use of machine learning algorithms applied
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, for the period from 2021 -2026. Reference: BI/UTAD/116/2025 Scientific area/research field: Engineering Researcher profile: First Stage Researcher (R1) Admission requirements: Degree in Computer Engineering