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, Mechanical, Electrical or a related field) Solid background in the energy domain, ideally with experience in various energy forms (electrical, thermal, etc.) Interest and skills in numerical modelling Fluency
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
knowledge graphs for predictive insights. Design feedback mechanisms to deliver interpretable outputs such as alerts, recommendations, and confidence scores. Validate system robustness using real-world
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reproductive isolation. This will largely advance our still limited knowledge on the intricate mechanisms of CHC perception in particular and on speciation mechanisms mediated by chemosensory evolution in
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of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Relevant industrial and / or research experiences Knowledge of plasticity, damage mechanics, and thermo
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robots will make current labour-intensive cultivation systems (e.g., stripcropping, targeted mechanical weed control, etc.) profitable, contributing to increased biodiversity locally and reducing the need
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the hydrogen industry Investigation of reaction mechanisms in the field of the hydrogen economy, particularly with regard to the charging and discharging of hydrogen carriers Cooperation with partners in
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public organisations operate and coordinate themselves and their relations with private parties in the construction industry. This PhD project aims to experiment with unique shared service centres
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of the mechanical properties of the cellular actin cortex, the biomechanics of cell division, and the coupling between cell shape and mechanics and cellular state / fate during cellular transitions. The successful
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student with an aerospace, mechanical engineering, or physics background. Experience of experimental and computational modelling of icing physics, instrumentation and imaging techniques would be