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the IDUN section, led by Prof. Anja Boisen at DTU Department of Health Technology (DTU Health Tech). IDUN is a highly cross-disciplinary research section with over 50 members that focuses on the development
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setting. Conduct process simulations using tools such as Aspen Plus, COMSOL, or equivalent software to predict system performance. Collaborate with engineering companies to develop a prototype carbon
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strategic initiative on AI method research within health data science. We aim at creating a cross-disciplinary initiative to strengthen cohesion across medicine, engineering and natural science disciplines
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, machine learning, electrical engineering, or a related field. The ideal candidate will have some of the following skills such as: Computer vision and machine learning: A solid understanding of image and
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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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scientific advice of the highest quality within building design and processes, building construction and safety, building energy and installation, solid mechanics, fluid mechanics, materials technology
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these intricate immunological processes. Using advanced bioengineering methods and innovative molecular tools, this project aims to: Develop robust 3D skin-on-a-chip models incorporating genetically engineered
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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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Infrastructure". If you have a strong background in managing technical projects, software engineering, and data science, this position offers ample opportunities for conducting cutting-edge health data science on