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for downstream applications such as mapping, simulation, analyses and other related uses. This PhD investigates methods to transform raw 3D data into structured scene representations that integrate
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data and archaeological signatures (e.g., circular mounds, linear ditches, rectangular foundations, etc.) tailored for AI applications – Feature engineering and representation learning to enhance
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, and the integration of compliance requirements into decision-making structures. It will combine doctrinal legal analysis with case studies and design-oriented methodologies in order to develop
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, Physics, Electrical Engineering, Communication Engineering, or equivalents; – Knowledge in artificial intelligence, statistical and machine learning, complex systems, agent-based modeling and simulation
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techniques, with a specific focus on symbolic model checking methods using satisfiability and satisfiability modulo theories solvers as symbolic reasoning engines. Importantly, in addition to researching novel