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< 14 1,5 < 14 1,0 < 14 2,5 A.2: Personal CV (using table A.2.), with a weighting of 70%; A.2. - Auxiliary table CV Scientific and Technological Knowledge Refers Does not refer 1. Knowledge in creating
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: • Have knowledge of data processing and analysis technologies. b) Preferential Factors: • Knowledge of programming languages for data analysis (e.g., R, Python); • Knowledge in Artificial Intelligence
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admissibility requirements: mandatory requirements: Knowledge of data analysis and exploitation. preferential factors: Knowledge of learning and knowledge extraction; Knowledge of Artificial Intelligence and
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year or its duration (star and term). Candidate admissibility requirements: mandatory requirements: Knowledge of data analysis and exploitation. preferential factors: Knowledge of learning and knowledge
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. Preferential Requirements: Knowledge of motion planning for robotic manipulators; Knowledge of robotics simulators; Knowledge in ROS. Admissibility requirements: It is essential, under penalty of not being
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have consolidated knowledge in: - Proven experience in data acquisition for Industry 4.0; - Knowledge of industrial networks and architectures - Knowledge of microcontrollers - Good reading, writing and
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from academic degree recognition processes. Specific Requirements - Knowledge acquired during academic training or education in: (i) database management; (ii) analysis of dietary data; (iii) experience
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have consolidated knowledge in: - Proven experience in Knowledge Extraction from Data (i.e. data analysis, data pre-processing); - Proven experience in C# and/or Python programming languages; - Good
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, the scholarship holder must make use of knowledge of data modelling, data storage and data processing. Support in the data modelling component, for the definition of the Domain Reference Model, is required. Work
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for applications, including those resulting from academic degree recognition processes. b)Preferred Factors • Knowledge in C programming language; • Knowledge in electrical signal acquisition. Applicants eligibility