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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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Applicants should hold a relevant MSc degree in electronics, electrical engineering, computer engineering, or related fields. Required Qualification: Solid background in digital CMOS design and deep learning
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(CIL) and contribute to open-source reproducible research. Together, we aim to push the boundaries of mathematical imaging data science, materials science and digital building technology
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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
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recognised academic environment with over 400 employees and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including
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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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research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural Technology. Our technologies and solutions are developed with the aim of benefiting
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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