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, Keras, and Scikit-learn and NumPy. Hands-on experience processing, analyzing, and visualizing scientific data obtained from analytical instrumentation, and working with datasets and databases are also
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, tables, and visual synthesis material to support discussions within the team and contribute to the consolidation of future science strategy documents; apply existing AI/Machine Learning tools to identify
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, navigation and control, visual landing and event-based vision, scientific deep learning for physical systems, spiking neural networks for event-based systems. Building on this experience, the research line
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