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(mechanical, electromagnetic, and, possibly, fluid-dynamic) and multi-scale simulations for drone components using finite element tools (e.g., Abaqus, Comsol). · Supporting the development of an AI
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Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process
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processing, and multiphysics simulation. During their study, doctoral students are encouraged to pitch and develop research ideas based their findings, novel publications, and emerging challenges in the field
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–specific ways, and their downstream biological effects remain poorly understood. This project tackles this fundamental gap — by building computational models that simulate what goes wrong in the brain, one
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for the accurate calculation of materials properties. You will combine methods from quantum informatics and solid-state physics to describe the complex electronic and ionic processes in battery materials. New
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challenges like AI, fake news, echo chambers, and political polarisation. The results will be new digital tools, analysis methods, and content types for the future of media. The centre performs research
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position We are looking for a PhD candidate for microfabrication, nanostructuring
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for mitigation and adaptation measures tailored to each specific context. Applicable law and regulations The call for applications and hiring process are governed by the provisions of Regulation no. 487/2020
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of Quantum Information Processing in Networks. The stipend is
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outcomes of complex reactive processes (e.g., electrolyte decomposition, biomass pyrolysis) via a combination of atomistic simulations and CRN ML Desired Qualifications: We are looking for candidates who