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Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of the Leiden Institute
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physics and building high performance imaging systems. She or he has a demonstrable interest in optics, signal processing, and mathematics or machine learning. The candidate should have an MSc degree in
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of coronary artery disease and supporting clinical decision-making during catheterization procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop
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machine learning and physics to recover nanoscale information from imperfect images? Modern computer chips are built with features only a few nanometers across, yet manufacturers need to measure these
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on the PhD projects you marked to be interested in. This will enable to make a final selection of your project in mutual consultation. Visit our website for more information about the application process or
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PhD Position on Predictive Plant–Microbiome–Pathogen Interactions Faculty: Faculty of Science Department: Department of Biology Hours per week: 36 to 40 Application deadline: 1 October 2026
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computer vision, deep learning, and logical reconstruction techniques. The research investigates how multimodal imaging modalities - including scanning electron microscopy (SEM), photon emission microscopy
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of abdominal aortic aneurysms. Information As a PhD candidate, you will contribute to the prestigious NWO VICI programme "(R)evolution in Abdominal Ultrasound Imaging" within the Photoacoustics & Ultrasound
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PhD in Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of
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fundamental learning procedures to tackle distressing images related to aversive memories. The aim is to generate insights with direct impact on clinical practice and patient wellbeing. PhD Candidate Reducing