161 structures "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" PhD scholarships in Norway
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- NTNU - Norwegian University of Science and Technology
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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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: 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
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of the position Numerical simulations of nonlinear photonic waveguides and devices Photonic design of hybrid integrated laser structures for manufacturing at NTNU or in collaboration with external foundries
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transactions; Ship design and construction; Voyage planning and optimization; Condition monitoring and maintenance; Crew training; Maritime traffic and ship surveillance; Decarbonization and energy management
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, the MSCA Doctoral Network project SAILING (https://Secure AI and Digital Twin Empowered Smart Internet-of-Energy ) aims to establish a multidisciplinary network of leading research groups and industrial
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possibility of extension) Start date: August 2026 at latest The students will be enrolled in the structured PhD programme in Computer Science at Sapienza University of Rome, Italy: https://www.uniroma1.it/en
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for health economic evaluation will be considered an advantage. The candidate should be able to work independently and in a structured manner, while also being capable of effective collaboration with others
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of the PhD project is to develop an effective control structure and real-time optimization scheme for a novel continuous bioprocess. The control and real-time optimization will then be validated in experiments
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Master’s degree. Please see https://hkdir.no/en for more information. The approval process will take some time and we recommend you to contact HK - dir as soon as you decide to apply for the position
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to evaluate and inform digital health interventions for women at increased risk of GDM. The project will primarily utilize data collected from a completed randomized controlled trial (https://bump2babyandme.org