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Field
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physics, materials science, computer science or a related discipline background in one or more of the following areas is desired: X-ray or electron imaging techniques, and image processing proficiency in
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, medical image reconstruction principles and experience with high-performance computer simulations in physics would be beneficial Experience in working with medical imaging data, especially with PET, and
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phenomena such as velocity and homogeneity in hierarchically porous Si?based materials conduct multiscale imaging using MHz X?ray projection imaging, X?ray micro- and nano-computed tomography, and scanning
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of short-axis MR image sequences. Training You will be based at the Vision Computing Lab within the School of Computing Sciences, which specializes in deep learning for medical image analysis and neural
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methodology to generate confidence in such decision, potentially reducing maintenance costs and down-time for offshore wind energy production. The images taken by each drone are loaded into the pre-processing
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 9 days ago
framework, medical image reconstruction principles and experience with high-performance computer simulations in physics would be beneficial # Experience in working with medical imaging data, especially with
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Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy | Austria | 17 days ago
5 Nov 2025 Job Information Organisation/Company Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy Research Field Computer science » Modelling tools
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to demonstrate consistent knowledge in areas such as structural monitoring and/or engineering mechanics and/or numerical modelling and/or data post-processing. The research activities will be performed within
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pathways. Are you ready to dive into the how, using cutting-edge imaging techniques? Then the Department of Earth Sciences is looking for you! We would welcome a highly motivated and ambitious applicant
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learning has strong potential for computer vision, from hyperbolic image segmentation [2] to hyperbolic tree embeddings [3] and hyperbolic vision-language models [4,5]. [1] Nickel, Maximillian, and Douwe