17 model-driven-engineering PhD positions at NTNU Norwegian University of Science and Technology
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process here. About the position The Department of Engineering Cybernetics at NTNU is offering upto 2 fully funded PhD positions in the area of data-driven decision-making for energy communities. Energy
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innovative approaches in bit technology, hydraulic hammer systems, drilling fluids, and thermal management. The project will combine experimental insights, physical modeling, digital‑twin technologies, and AI
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. You will explore how emerging AI technologies—foundation models, generative design tools, agent platforms, reasoning engines, and reinforcement learning—can be adapted and extended for maritime design
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approaches for identifying, modelling, and integrating uncertainty factors originating from IoE devices and system dynamics, combining data-driven learning with knowledge-based modelling techniques
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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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Engineering at NTNU, where computational mechanics, advanced finite element modelling, and artificial intelligence meet. As a PhD candidate, you will work at the forefront of nonlinear simulation, contributing
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13 Mar 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Ocean Operations and Civil Engineering Research Field Computer science
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, physics-based models, and data-driven methods to support design, manufacturing, and decision-making across aluminium value chains. Education and competence building are central pillars of FAST. The centre
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application process here. About the position The Department of Information Security and Communication Technology invites applications for a fully funded PhD position on AI-driven network operations for cloud
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knowledge of AI-enhanced planning in shipbuilding supply chains. Apply quantitative methodologies, such as simulation, analytical modelling, and AI‑driven techniques, to develop decision support for efficient