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experimental methods, as current technology only facilitates static imaging. As a PhD student at TU Delft, you will develop the methods to bring about a step change in dynamic imaging of biomolecular processes
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on mammography. To achieve this goal the following work packages are proposed: i) development of a PCCT scan protocol for breast imaging: a phantom study, ii) optimization of PCCT scanprotocol and development of a
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Challenge: Ultrafast imaging of biomolecular processes at high resolution. Change: Combining single-molecule fluorescence microscopy and cryo-EM/ET. Impact: Driving a profound understanding of life
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advanced quantitative image-based analysis to tailor personalized treatment and diagnostics. Our pathology department is renowned for its deep learning-based image analysis research, leveraging international
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methods that can process Imaging radar data on resource-constrained devices, and perform standard automotive perception tasks, such as object detection and collision prediction. Moreover, due to the real
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with Lewy bodies (DLB), non-invasive imaging biomarkers are continously in development to contribute to better diagnosis, prognosis and treatment strategies. The aim of the proposed project is to define
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, this requires the development of novel deep-learning methods that can process Imaging radar data on resource-constrained devices, and perform standard automotive perception tasks, such as object detection and
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are pioneers in developing advanced concepts of computational imaging, a marriage between cleverly designed imaging systems and sophisticated post-processing. In everything we do, there is a core of cutting-edge
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Your main task will be to develop new methodologies for the application of machine learning and deep learning on medical images for the purpose of disease diagnosis and outcome prediction. This will be
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recovered, but scale up in a context of meaningful biopolymer applications stands to have significant bearing on the success of the industrial process. In this project, the focus is on relevant PHA