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Field
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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
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The Cell Microscopy Core at UMC Utrecht is an expertise center for microscopy at the subcellular, cellular and tissue level. CMC provides advanced imaging services combining fluorescence, live-cell
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biomedical image processing. Within the scope of machine learning and computer vision, there will be freedom to suggest your own research directions, and to become acquainted with new techniques and approaches
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directly to the upstream swt-initiative31/skija prototype, focusing on: rendering logic. layout behavior. and basic widget implementations. In parallel, they will evaluate how the Skija backend could be
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myeloma, as well as to understanding immune aging processes, through comprehensive functional, phenotypic, and genetic analyses of large, dedicated patient biobanks. To elevate our research to the next
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protocols and have affinity with medical topics. You have knowledge of CT dosimetry and radiation physics. You have good experimental skills and experience with image processing. You have some knowledge in
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, you will have experience with acquisition and processing of tomographic images, rock mechanics, machine learning and/or numerical modelling. Given the highly diverse nature of the research groups
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system performance and calibration. This also involves the development of prototype SAR and SAR interferometry (InSAR) data processors and the Calibration and Performance Analysis Facility (CPAF). Sentinel
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/Julia) are essential. Ideally, you will have experience with acquisition and processing of tomographic images, rock mechanics, machine learning and/or numerical modelling. Given the highly diverse nature
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Postdoc Development of a Low-Voltage Multi-Beam SEM for High-Throughput Imaging | TU Delft Job description Scanning Electron Microscopy (SEM) plays a central role in today’s nanoscale imaging across