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at the Division of Cell Biology, Neurobiology and Biophysics external link within the Department of Biology external link . Our division hosts the state-of-the-art Biology Imaging Center external link , which
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
, segmentation, and severity quantification. The performance of AI models will be assessed across different impact energies, materials, and boundary conditions. Cranfield University is uniquely positioned
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focus on image processing and restoration, to develop novel AI-based approaches to restore and denoise Transmission Electron Microscopy (TEM) images. This position is part of a cross-disciplinary research
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nanotechnology, with access to state-of-the-art instrumentation for HAADF-STEM imaging and in situ experiments. The project will be pursued in close collaboration with the Materials Design Division (also at IFM
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to advance 3D imaging methods for neuroscience. Your colleagues: An interdisciplinary team working across the Cognitive Neuroscience Department and the Mental Health and Neuroscience Research Institute
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, or erroneous data, Data cleaning and generation, Development of enhanced loss functions and information-theoretic methods for optimized data analysis, Machine learning-based image segmentation of tomographic
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. Besides this, you will work on scene understanding using RGB and possibly thermal and radar images, including based on object detection and image segmentation, and collaborate effectively with other
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for non-invasive brain imaging techniques such as fNIRS or fMRI. With the constantly improving spatial resolution of these methods, a thorough knowledge of potential differences in vascular architecture
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division at the Department of Physics, Chemistry and Biology (IFM). EMM conducts leading research in advanced electron microscopy for materials science and nanotechnology, with access to state-of-the-art
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will work on scene understanding using RGB and possibly thermal and radar images, including based on object detection and image segmentation, and collaborate effectively with other technical partners who