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W3 Endowed Professorship for “Hemodynamic Modeling in Atherosclerosis- (f/m/d) KSB Foundation W3 end
state-of-the-art imaging techniques with software-supported analysis of flow dynamics and mathematical modeling for the precise characterization of hemodynamic mechanisms in atherosclerosis. In research
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out independent as well as collaborative research in the area of Ultra-High Field Magnetic Resonance Imaging (MRI). The position involves the development of 7 Tesla MRI methods and applications
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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lung health, across a range of laboratory and imaging programs. Role Summary This role will help to develop lung function-based respiratory biomarkers through AI, machine learning and image processing
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activity on in-situ and operando study by coupled techniques: Electrochemistry/Raman, Electrochemistry/NMR, Electrochemistry/X-ray diffusion, imaging and spectroscopy. The MIEL team is consisting of 19
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biostatistical analysis. Process imaging data to perform blood flow analysis. Maintain Aortic Center database. Discuss the results with the PI and other lab members. Attend/present at seminars and conferences, and
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experience with imaging, image processing, and/or visualization, as well as excellent programming skills. You must have a relevant Master's degree in computer science, electrical engineering, imaging science
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, Excel, PowerPoint) Adobe Illustrator and Photoshop or similar image processing software Basic knowledge and practical experience in the operation of high-resolution mass spectrometers (preferably Orbitrap
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-laboratory.com/ Center for Innovation in Imaging Biomarkers and Integrated Diagnostics (CIMBID): https://www.cuimc.columbia.edu/news/new-columbia-center-will-leverage-ai-enhance-patient-care Department
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with archival best practices, including those related to research, processing, and/or digitization; basic familiarity with current approaches to digitization, image manipulation, file management, and/or