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are required and will be given. You will have an exciting opportunity to work on the future paradigm for the construction of multistorey buildings in which a comprehensive system-of-systems approach intertwines
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of image recognition tools, statistical analyses and the mechanistic description of carbon substrate conversion and growth on solid material. The tasks also include process-related life cycle analyses
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. The aim of the project is to bring about a paradigm shift in the design of switchable materials, by delving into the uncharted territory of f -element valence change (VC). The VC materials will be
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to identify and visualize long-term patterns in blood glucose among people with insulin-treated type 2 diabetes. Moreover, the PhD fellow will include development and testing of a prototype user interface in
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facilities and state-of-the-art equipment for material preparation, characterization, indoor air quality assessment, and prototype development. Responsibilities and qualifications You are enthusiastic and self
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. Programming skills in Python, with experience in deep learning frameworks such as TensorFlow or PyTorch. Experience with computer vision techniques, image processing, and neural networks. Familiarity with
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) within Robotics, Computer Vision, Computer Science or similar and the candidate is expected to have a profound knowledge on the majority of the following topics: Image processing/computer vision Deep
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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
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Job Description In this project, you will develop new ways to study cancer using Magnetic Resonance Imaging (MRI) of various nuclei. The studies so far have been using Positron Emission Tomography
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classical precision limits for metrology and imaging, Fundamental tests of quantum mechanics, exploring macroscopic quantum phenomena. Continuous variable quantum opto-mechanics Explore quantum control