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the forefront of research in organic chemistry. You will work alongside highly skilled and motivated group members in an enthusiastic and goal-oriented atmosphere. We welcome talent from all over the world
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on recent advances in Higher-Order Mathematical Operational Semantics, a pivotal generalization of Turi and Plotkin's seminal approach to structural operational semantics. We seek an apt and motivated PhD
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PhD scholarship in Biomaterials-based Approach for the Creation of Artificial Red Blood Cells - D...
-edge techniques (e.g., electron/confocal microscopy, flow cytometry, DLS, FTIR) Join a highly supportive, international team where your ideas are welcomed, and your growth is prioritized Work at DTU
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supportive, international team where your ideas are welcomed, and your growth is prioritized Work at DTU Health Tech, one of Europe’s top technical universities, located just outside Copenhagen—a global hub
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-performance virtual testing and cutting-edge digital technologies? Do you want to contribute to the scientific development of structural virtual testing and digitalization? A Tenure Track Researcher position is
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support in manufacturing and production Research area and project description: We are looking for 3 PhDs to work on Digital Twins for autonomous systems in industrial manufacturing settings. In industrial
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Adoption of Artificial Intelligence for Software Engineering in Denmark”. The stipend is open for appointment from 1 October 2025 or soon hereafter. The duration of the position is three years. Your work
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, as well as analyze kinetics and stability of such systems. The collaboration will include planned visits to Australia and Sweden as part of the work. The majority of the work will be experimental, but
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are required and will be given. You will have an exciting opportunity to work on the future paradigm for the construction of multistorey buildings in which a comprehensive system-of-systems approach intertwines
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Post doc position in theory of machine learning at Department of Computer Science, Aarhus University
is on understanding and improving the performance of classic learning algorithms, in particular Boosting and Bagging, both in terms of speed and generalization capabilities. The project also allows