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modern control theory (PID, adaptive, robust, and fractional control); Experience with fuzzy logic and AI-based control (reinforcement learning, neuro-fuzzy systems); Skills in modelling and simulation
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. Candidates must demonstrate solid knowledge of relevant social science theories and methods necessary to carry out the proposed PhD project. Admission to the faculty’s PhD programme is a prerequisite. See
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the humanities or other relevant fields may be considered on an individual basis. Candidates must demonstrate solid knowledge of relevant social science theories and methods necessary to carry out the proposed PhD
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demonstrate solid knowledge of relevant social science theories and methods necessary to carry out the proposed PhD project. Admission to the faculty’s PhD programme is a prerequisite. See admission
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fields may be considered on an individual basis. Candidates must demonstrate solid knowledge of relevant theories and methods necessary to carry out the proposed PhD project. Admission to the faculty’s PhD
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relevant fields may be considered on an individual basis. Candidates must demonstrate solid knowledge of relevant social science theories and methods necessary to carry out the proposed PhD project
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: Strong expertise in signal processing for wireless communication systems, including modulation and coding techniques on the physical layer of a radio, array antennas and their use in multiple input
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theory & experiment: Co‑design validation experiments with experimentalists; iterate models using feedback from new measurements. Automate the workflow: Build Python workflows for simulation and data
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& advance digital twins: Integrate electronic structure (e.g., DFT, ab initio MD, tight-binding) with multiscale simulations to predict experimental observables at interfaces. Bridge theory & experiment: Co
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the Norwegian Centre for Mathematics Education and researchers at the University of Washington. So far, we have found that the ØDU methodology helps students bridge the gap between theory and practice, which is