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Field
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, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast
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Experience with numerical simulation, statistical estimation, or probabilistic modeling. Programming proficiency (Python, Matlab or C++), especially for numerical experiments. Interest in connecting theory
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, patient travel times, regional variations, and treatment patterns. Simulation Modelling: The candidate will develop and apply simulation models to evaluate the effects of centralizing care on measures
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and heat transfer in geothermal systems under high-pressure and high-temperature conditions relevant to AGS. • Developing high-fidelity direct numerical simulation (DNS) models to map
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its rich information content, conventional analysis methods have not yet fully realized its potential. This research project aims to develop a robust AI foundation model based on modern Transformer
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reduces computational cost and enables large-scale reactor simulations, current porous approaches, based on Reynolds-averaged Navier-Stokes models, rely on empirical correlations and assumptions that may
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for climate-positive and CO2-negative processes. What you will do Optimization of the pilot plant for the combustion of solid fuels (biomass, waste) with oxygen and subsequent CO2 capture Development of models
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., temperature, humidity, collision processes) that influence fragmentation. Develop and validate a numerical model to simulate raindrop-freezing fragmentation and its contribution to secondary ice production
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on the following criteria: Knowledge in electric power engineering, power electronics, and power system analysis Experience in modelling, simulation, and experimental work Proficiency in Swedish and English, both