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ensuring the security, integrity, and efficiency of all active systems and services. This requires a deep understanding of system architecture and involves the expert configuration of core network services
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, investment project nº 54, team, in the context of PPS10: Neural network-based systems for robot application, PRR-GA-PPS10-DIGI2, team, namely developing supervised R&D works, monitoring technical meetings with
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the activities carried out in Activity 3 dedicated to the implementation of a demonstrative network of Montados and Dehesas. Specifically, in the creation of a common methodology for assessing environmental
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the framework of the M-ERA-NET3 network “ERA-NET Cofund in raw materials, under the following conditions: Scientific Area: Mining Engineering Admission requirements: Candidates who cumulatively meet the
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) Knowledge of machine learning techniques, with an interest in exploring algorithms such as regression, decision trees, Random Forests, and neural networks. b) Basic programming experience in Python and
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13 (5 points); Bachelor Degree classification lower than 13 (2 points); B. Knowledge of Cyber-physical Systems, Automation, CAN Communication Protocol, Machine Learning, AI, Sensor Networks
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) Knowledge of machine learning techniques, with an interest in exploring algorithms such as regression, decision trees, Random Forests, and neural networks. b) Basic programming experience in Python and