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Field
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performance checks. Monitor scans and troubleshoot basic operational issues during imaging. Reconstruct CT scan datasets using appropriate reconstruction software. Perform image processing, segmentation, and
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data Conclude the study in journal publications and patent filing Job Requirements PhD from Chemical and Biomedical Engineering, Optical Engineering, Signal Processing, Precision Instrument, Information
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advertisement The position A PhD position is available at the Department of Automation and Process Engineering (IAP), Faculty of Engineering Science and Technology in advanced microscopy methods for bioimaging
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learning, as well as in digital signal processing and acoustic imaging. The group includes around 20 postdoctoral researchers and PhD research fellows funded by a range of national and international agencies
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machine learning, computer vision, and medical image analysis, with publications in top-tier AI and medical image analysis conferences and journals, including CVPR, ICCV, ECCV, NeurIPS, MICCAI, TPAMI, TIP
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data Conclude the study in journal publications and patent filing Job Requirements: PhD from Chemical and Biomedical Engineering, Optical Engineering, Signal Processing, Precision Instrument, Information
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into prototype systems with practical application potential. Contribute to fabrication process optimization, device prototyping, data interpretation and technical documentation for project milestones and
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activities. You must have a PhD or equivalent in Biology, Palaeontology or another relevant subject area and proven knowledge of mammalian anatomy and evolution. Experience in working with morphological image
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image analysis, that is medical images that evolve over