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of programming and artificial intelligence.; - Knowledge of deep learning and computer vision.; - Autonomy. Minimum requirements: Strong knowledge of the English language (written and spoken). 5. EVALUATION
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.; - Develop skills in artificial intelligence and machine learning techniques for analyzing operational data and detecting anomalies, using foundational model approaches (e.g., GridFM project, LF Energy
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with a focus on traditional machine learning (shallow learning) and deep learning methodologies. Knowledge of Data Science, including the development of data analysis and visualisation pipelines. 5
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, algorithms with a focus on traditional machine learning (shallow learning) and deep learning methodologies. Knowledge of Data Science, including the development of data analysis and visualisation pipelines. 5
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of Machine Learning techniques. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first phase comprises the Academic Evaluation (AC), based