14 information-security "https:" "https:" "https:" "https:" "https:" "Dr" "Robert Gordon University" PhD positions at Tallinn University of Technology
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a strong emphasis on AI-driven security, digital twins, and real-time situational awareness. The position is part of a multidisciplinary research effort combining cyber security, maritime systems
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, including optical measurements, metrology, and chemical analysis, providing a solid foundation for innovation in materials engineering. Additional information For further information, please contact Dr
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For further information, please contact jiri.strouhal@taltech.ee and tarmo.kadak@taltech.ee and visit https://taltech.ee/en/department-business-administration and https://taltech.ee/en/phd-admission Where
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The information 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 francesco.deluca@taltech.ee CV Motivation letter
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managed to successfully explain the results to wider society and to convert research outcome into practical technologies and applications. For further information, please contact Prof Dr Tarmo Soomere
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) in cooperation with the Faculty of Engineering. It has established research groups in areas such as – Blue economy & aquatic resources, waterways safety management, nautical sciences, green maritime
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. For further information, please contact Prof Dr Tarmo Soomere tarmo.soomere@taltech.ee and/or Dr Katri Viigand katri.viigand@taltech.ee or visit https://wavelab.taltech.ee Work Location(s) Number of offers
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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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transmission of diagnostic data to cloud-based platforms for further analysis, visualization, and integration with digital maintenance workflows. Particular attention will be given to data security, integrity
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on integrating sensor-driven data streams and historical datasets into the hybrid digital twin framework, thus enhancing the reliability, safety, and efficiency of SDVs throughout their lifecycle—from design and