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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
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documentation such as: certified copy of admission to a PhD programme programme summary of approximately one A4 sized sheet including information about your PhD project, topic, method, theoretical approach, and
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systems, bit design, drilling fluids, and downhole thermodynamics, this position will contribute to new methods that improve drilling efficiency, reduce costs, and support the development of deep geothermal
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This is NTNU NTNU is a broad-based university with a
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
Duties of the position Conduct original research on microstructure evolution during extrusion of scrap-based aluminium alloys, both experimentally and numerically Develop and implement computational
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numerical and data-driven method will be exploited in this project to systematically integrate natural design principles into the development of bioinspired materials. Particularly, artificial intelligence
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the mandatory PhD research education programme Develop a hybrid numerical and data-driven method to integrate natural design principles into the development of bioinspired materials Perform independent, high
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. Integrating numerical models tailored to Southern Norway and Greenland with existing datasets to investigate how their landscapes have formed. Presentation of results at international conferences. Publication
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dedicated to the study of all aspects of concrete. Our research interests range from the material to the structural level and are based on theoretical, numerical, and experimental investigations. The PhD
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computational engine of Artificial Intelligence (AI), and therefore it is a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories