12 evolution "https:" "https:" "https:" "https:" "https:" "https:" "University of Texas at Austin" PhD positions at Tallinn University of Technology in Estonia
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for Smart Cities of Tallinn University of Technology (TalTech) invite applicants for a 4-year PhD position in the field of responsible AI governance for smart city development. The project focuses on how
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development of a scenario-based platform. Applicants should fulfil the following requirements: Master’s degree in architecture or civil engineering. Clear interest in the topic of the position. Excellent
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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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opportunities for career development, prospective students can visit the TalTech Estonian Maritime Academy´s official website or LinkedIn page. How to apply The information for the PhD admission is available
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at TalTech´s web-page: https://taltech.ee/en/phd-admission The application should include: A motivation letter describing your research interests Curriculum Vitae (CV) Copies of academic transcripts and
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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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coastal area. This will allow more robust estimates of long-term trends in eutrophication indicators, support the development of more targeted measures to achieve good environmental status of the Baltic Sea
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nearshore structures and contribute to sustainable coastal management. References Eelsalu, M., Parnell, K.E., Soomere, T., 2022. Sandy beach evolution in the low-energy microtidal Baltic Sea: attribution of
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: The information for the PhD admission is available at TalTech´s web-page: https://taltech.ee/en/phd-admission A motivation letter describing your research interests Curriculum Vitae (CV) Degree certificates as
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industrial applications has accelerated the development of AI- and IoT-enabled condition monitoring systems. Previous research in this domain has successfully demonstrated the feasibility of IoT-based data