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a completed doctoral education up to an obtained doctoral degree. For many important applications, data is represented as graphs, with dynamic relationships between nodes. Examples include the power
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language and educational competence courses if required. The candidate will join and become part of an internationally leading research environment in quantum condensed matter theory and experiments
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to develop generative AI methods that are applicable for data types beyond text and images (e.g., dynamic graphs), and the successful candidate will be given high level of independence when it comes
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. If you do not have letter grades from previous studies, you must have an equally good academic foundation submit a short project proposal outlining the proposed topic, research questions, theory, methods
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systematic study of Dirichlet series from the point of view of modern operator-related function theory and lies in the intersection of complex analysis, operator theory, and analytic number theory. The main
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demanding PhD courses. Both potential flow theory and CFD will be applied. There are also possibilities for conducting model test. As a PhD Candidate with us, you will work to achieve your doctorate, and at
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University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Excellent computation skills Background in Structural Reliability Theory Background in
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theory (state observers, parameter identification), mathematics of partial differential equations, modelling and simulation, machine learning/reinforcement learning. Experience with design of state- and
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forces with 15 partners from industry, universities, and research institutes. Research areas cover competences that the Norwegian industry needs to develop cutting-edge theories, methods and technology
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. Research areas cover competences that the Norwegian industry needs to develop cutting-edge theories, methods and technology, for efficient, effective and responsible exploitation of data-driven AI in