193 structures "https:" "https:" "https:" "https:" "https:" "The University of Manchester" PhD positions in Norway
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
aluminium of high recycled content. The use of post-consumer scrap (PCS) in structural components (e.g. for automotive applications) is expected to increase with growing sustainability demands. Understanding
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/ML methods to improve drillability, increase rate of penetration (ROP), reduce non‑productive time, and enable cost‑effective geothermal well construction. The work includes evaluating geothermal
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Structure (BETTER)”, and this PhD project specifically aims at developing a unified, scalable, and interpretable framework for tensor analysis. Specifically, the project will: Develop novel, modular
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-funding from industry and academic partners. You can read more about NICE on https://www.ntnu.edu/nice. Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research
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well as researchers from 15 international institutions. More on the project at http://sure-ai.no . Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality
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the ability to work independently and in a structured manner, while also being capable of effective collaboration with others. The applicant must exhibit both the ability and motivation to undertake a PhD
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Technology . The position is for a period of 3 years. Desired start date: 1 May 2026 or earlier. The fellowship is part of TIES project “Tunable ion separations with micro-structured composite membranes
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arising from the inclusion of scrap, and to control the processing parameters such that the structural integrity of the cast components can meet with the demands to performance. The starting date is August
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and analytic structures for the analysis and modelling of complex sequential data. Path signatures, originating in stochastic integration and rough path theory, provide expressive representations
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: Digital twin development for heritage risk preparedness AI-based predictive monitoring (humidity, flooding, structural stress) Integration of GIS/BIM, LiDAR and IoT telemetry Federated data architecture and