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wireless system. Analyse experimental measurements using MATLAB, Python or equivalent computational tools. Compare experimental measurements with modelling or theoretical predictions generated by the wider
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of Marine Technology at NTNU has a vacancy for a PhD Candidate in Deep Learning enhanced FSI modelling of Multi-modular Floating Structures. The position is part of the AIMOS project (Artificial Intelligence
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developing simulation flows, analysis methodologies, and predictive models that enable Design-Technology and System-Technology Co-Optimization (DTCO/STCO) studies for future systems. You will work closely with
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rules for ceramic shell mould clusters; Experimental validation of the relationships between microstructure and thermal shock resistance; Development of multi-scale finite element models for predicting
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reliably assess fatigue damage and predict remaining lifetime, enabling proactive maintenance strategies that extend service life and reduce CO2 emissions. Through this PhD scholarship, you will contribute
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interferometry, etc.), (v) Predictive modelling of coupled phenomena (reactive transport, rock-water interactions, etc.), (vi) Uncertainty quantification (Monte Carlo, meta-modelling), and (vii) Risk analysis. The
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work closely with an interdisciplinary team spanning microbiology, engineering, and computation, and will contribute to developing predictive models that link bacterial physiology to infection outcome
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on temporal data (predictive maintenance, sensory processing for robot control, etc), in which efficient on-device processing is crucial. We are looking for a highly motivated PhD candidate with an interest in
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at the Laplace laboratory, where numerical and analytical models are being developed to predict plasma potential control and flux entrainment from polarized electrodes. During the third year of the thesis project
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methodological comparison between mechanistic vector control models and macroscopic SIR-type models calibrated on serological survey data. Currently, risk indicators (e.g., R₀ estimation) derived from mosquito