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the synchrotron-based imaging technique Dark-Field X-ray Microscopy and together we utilize it to visualize the evolution of internal structures in metals during plastic deformation, i.e. changes in shape due
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complete picture of fish habitat use and connectivity. The PhD is part of the section for Ecosystem based Marine Management and the Marine Habitats research group, as well as several synergistic initiatives
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described through five overall research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural Technology. Our technologies and solutions are developed
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of electron microscopy imaging and spectroscopy to reveal the structure–property relationships that govern molecular adsorption mechanisms. This interdisciplinary project is fully funded by DTU’s PhD grant
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: Specialization in machine learning and computer vision. Strong skills in developing computer vision and AI models. Experience with thermography or thermal imaging. Experience in data fusion and multimodal learning
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thermochemical TES. Your main supervisor will be Prof Adriano Sciacovelli and you will join the Thermal Energy Section at DTU Construct. Your work will contribute to a paradigm shift in how complex TES systems
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described through five overall research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural Technology. Our technologies and solutions are developed
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innovative services and products which benefit people and create value for society. DTU Health Techs expertise spans from imaging and biosensor techniques, across digital health and biological modelling
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TotalEnergies. You will be enrolled in DTU’s Section for Oceans and Arctic and assume a dual role: (1) Systems Engineer able to design and prototype an integrated in‑situ observing platform that supports marine
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for the globally expanding healthcare sector with its demands for the most advanced technological solutions. DTU Health Tech’s expertise can be described through five overall research areas: Diagnostic Imaging