11 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" PhD scholarships at Tallinn University of Technology
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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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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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) extremes, preventive methods for mitigation of marine-induced hazards, application of machine learning techniques and opportunities provided by AI. Even though the listed advanced topics are mostly at the
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conducting simulator-based experiments, collecting and analyzing human performance and psychophysiological data, and developing models of human–machine collaboration for safe and efficient navigation
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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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statistics of mean and extreme wind events over the Baltic Sea region. Tellus A, 67, 29073. https://doi.org/10.3402/tellusa.v67.29073 Björkqvist, J.-V., Lukas, I., Alari, V., van Vledder, P.G., Hulst, S
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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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for mitigation of marine-induced hazards, application of machine learning techniques and opportunities provided by AI. Even though the listed advanced topics are mostly at the cutting edge of fundamental research
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The information for the PhD admission is available at TalTech´s web-page: https://taltech.ee/en/phd-admission . Please submit your application, with all your application documents to Professor Luca Mora (Luca.Mora
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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