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environment The Brain Imaging & Neuro Epidemiology group (BraINE) develops advanced methods for medical images analysis, combining computer vision, radiomics and deep learning approaches. The team has a double
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Wu Tseng. The BIG-CT research laboratory is focused on design and development of X-ray based imaging systems, imaging techniques, image processing, and image analysis, with an emphasis on clinical
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research protocols and procedures, including in computational tasks where data visualization, preprocessing, or interpretation can be improved. Devises and deploys custom machine learning approaches where
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Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy | Austria | 7 days ago
machine learning models for detecting subtle, clinically relevant changes in arthritis imaging. Create robust algorithms for longitudinal disease monitoring and treatment-response prediction. Build a
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related field) with a specialization in image processing and machine learning. They should demonstrate strong algorithmic programming skills (in Python, and possibly C++) and be comfortable working with
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instruments and modalities based on diagnosis. Knowledgeable in computer software for all imaging modalities. Independently performs standardized imaging protocols based on diagnosis. Competent in stereopsis
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, involving expertise in optics, electronics, image and data processing, chemistry, and biology. With the support of several European funding programs, the team is building a data science and machine learning
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are template based and all US measurements are auto-populated into templates for increased accuracy and efficiency. Fourteen fellowship-trained, subspecialized expert faculty perform both image interpretation
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About Us The applicant will join the new Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will
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motivated researcher. Project Ptychographic imaging offers valuable insights into both the properties of non-carbon materials and biological processes that are label-free. However, current microscope systems