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. The proposed PhD thesis topic: "Development of an AI-Powered Digital Twin for Dynamic Analysis of Drawing Tests: Exploring Fatigue and Educational Influences" Supervisors: Tenured Associate Professor
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to develop specialized deep learning architectures for analyzing drawing tests and human finger motions, with applications in diagnostics, cognitive assessment, and fatigue detection. The Ph.D. candidate will
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and sustainability of research and teaching in the fields of environmental geology, climate science and hydrogeology at TalTech. Content of work The content of work is a balanced amount of professional
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the field of hardware verification, lead and manage its activities and engage in balanced teaching and research activities. Tasks: conducting and organisation of research and development in the field and
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section 3), specialisation in electrical engineering. The goal of the position is to ensure excellence in the field of electrical engineering at Tallinn University of Technology, including teaching
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coordination of research activities. Experience in teaching and supervising at all levels (BSc, MSc and PhD level; executive trainings). Successful supervision of one or more doctoral theses. Active
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, analysis, and mapping for data collected in extreme environments. The main aim of this project is to develop state-of-the-art data analysis and mapping methods that are efficient, reliable, and near real
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of abstraction. The goal of this post is to develop a theory of composable crytpgraphic/cybersecurity protocols akin to the work of Broadbent and Karvonen [1], building on an appropriate selection of underlying
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in synthetic organic chemistry, especially in relation to asymmetric organocatalysis and borane catalysis, along with pertinent analytical (NMR, HPLC) skills. In addition, the candidate will develop
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for Digital Forensics and Cyber Security and have the opportunity to contribute to teaching. CONTEXT Large language models (LLMs) using generative methods have marked another milestone in the development of AI