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critical maritime operation or system Collecting and curating operational and security-related data for AI-based threat analysis Training AI and machine learning models for anomaly and threat detection
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friction. Coastal Engineering, 53(2), 149–165. https://doi.org/10.1016/j.coastaleng.2005.10.005 Dean, R. G., & Walton, T. L. (2010). Wave setup. In Y. C. Kim (Ed.), Handbook of Coastal and Ocean Engineering
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performance data using recommended guidelines and machine learning tools Defining the uncertainty sources Enhancing existing guidelines for full-scale power-speed assessment practice Disseminating research
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beneficial: Working knowledge of statistics and usage of MATLAB or other software for statistical analysis; Experience with machine learning and data mining. Good Estonian language skills Application procedure
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changes to hydrometeorological forcing. Geomorphology, 414, 108383, https://doi.org/10.1016/j.geomorph.2022.108383 Eelsalu, M., Viigand, K., Soomere, T., Parnell, K., 2024a. Systematic analysis
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integrating modeling, machine learning (ML), and advanced control methodologies. The research will focus on designing AI-driven algorithms to assess battery health, predict degradation trends, and optimize
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incorporate optimized machine learning algorithms, support standardized IoT protocols, and be validated in laboratory and semi-industrial environments. The project contributes to smart maintenance strategies
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urban design with microclimate simulations and measurements, GIS and Digital Twin technologies, and machine learning. The work will be part of a Horizon pilot project aimed at realizing a scenario-based