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PET tracer, and their ongoing (pre)clinical translation, Groningen is taking the lead in imaging of Gram-positive infections. This PhD project will focus on expanding this initiative to the imaging
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or computer vision. A critical understanding of AI model development and evaluation, including the capabilities and limitations of generative AI and synthetic data. Experience with image analysis, synthetic
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27 Sep 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
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Job description Next generation automotive imaging radars provide increasingly rich 3D information, opening the door to more advanced scene understanding and perception tasks such as 3D object
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combines microfluidics, bubble physics, and ultrasound signal processing to bring nanobubble imaging closer to clinical use. You will collaborate closely with a fellow PhD candidate, a postdoc, and a
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knowledge of MR physics Experience with signal processing and/or image processing Experience with Linux systems and High Performance Computing Good oral and written presentation skills in Norwegian
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for the position. Preferred selection criteria Experience with machine learning and neural networks Basic knowledge of MR physics Experience with signal processing and/or image processing Experience with Linux
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of novel volumetric representations and computational imaging methods for paired visible-light and X-ray images, as well as extending computer vision techniques from the visible-light RGB photography domain
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deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
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the development of novel volumetric representations and computational imaging methods for paired visible-light and X-ray images, as well as extending computer vision techniques from the visible-light RGB