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: Enhancing full-scale power-speed assessment reliability by using IoT and big data management Summary This PhD research focuses on uncertainty challenges caused by various disturbances (wind, wave, current
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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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Engineering and Mechatronics. The Proposed PhD thesis topic: “Intelligent Diagnostics of Electrical Machines through AI-Enabled IoT Systems: Design of Custom Embedded Hardware and Protocol-Aware Architectures
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the eastern coast of the Baltic Sea. Journal of Marine Systems., 129, 96–105, https://doi.org/10.1016/j.jmarsys.2013.02.001 Responsibilities and (foreseen) tasks Collection and processing of wave data, sea
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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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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
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for the PhD admission is available at TalTech´s web-page: https://taltech.ee/en/phd-admission The following application documents should be sent to tarmo.soomere@taltech.ee CV Motivation letter Degree