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Duration Including Renewals: 6 months Objectives Definition of a methodology for identifying cracks in concrete structures, based on computer vision algorithms. Application and validation on the viaduct over
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 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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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 days ago
, reference no. 2023.18249.ICDT, financed by national funds through FCT/MCTES (PIDDAC Workplan: Development of new algorithms based on statistical analysis for the detection of bursts in water distribution
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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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will be processed by advanced Artificial Intelligence algorithms. The numerous tasks for this grant will contribute to the project's activities. Namely: Installation of sensors on telecommunications
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will be processed by advanced Artificial Intelligence algorithms. The numerous tasks for this grant will contribute to the project's activities. Namely: Installation of sensors on telecommunications
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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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programme Reference Number AE2026-0003 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0003
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
the replicator equation. The focus will be on understanding the principles and number of coexisting species, and the quality of their dynamics. The candidate(s) will also apply data fitting algorithms/machine
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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