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of Sciences is looking for a full-time (100%) doctoral scholarship holder in the field of medical image processing and analysis using deep learning. This position is part of the ERC Consolidator project “A data
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in the field of medical image processing and analysis using deep learning. This position is part of the ERC Consolidator project “A data-driven approach to microstructure imaging” (ADAMI), funded by
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in the field of musculoskeletal magnetic resonance imaging Position Background: Magnetic resonance imaging (MRI) is key for diagnosing musculoskeletal (MSK) injuries and monitoring after therapy
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-driven approach to microstructure imaging” (ADAMI), funded by the European Union. ADAMI is a highly interdisciplinary project that combines insights from physics/engineering (imaging and image processing
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project that combines insights from physics/engineering (imaging and image processing of MRI and light-sheet microscopy), biological and medical sciences (tissue microstructure, immunostaining, and
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intelligence) to achieve a breakthrough in microstructure imaging with MRI. Position You will focus on the acquisition, processing, curation, and modeling of quantitative MRI data of healthy human brains and
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intelligence) to achieve a breakthrough in microstructure imaging with MRI. You will focus on the acquisition, processing, curation, and modeling of quantitative MRI data of healthy mice and mice models
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. ADAMI is a highly interdisciplinary project that combines insights from physics/engineering (imaging and image processing of MRI and light-sheet microscopy), biological and medical sciences (tissue
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use advanced hemodynamic, imaging, and molecular techniques to unravel the pathophysiological role of FAP, as well as to study the role of FAPIs (radiolabeled derivatives of a potent FAP inhibitor) as
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develop and apply low-dose TEM techniques such as exit wave reconstruction and integrated differential phase contrast imaging to investigate CsPbI3 thin films without electron beam damage. You will expand