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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | about 1 month ago
vivo models of PD Apply and further develop methodologies such as disease modeling, virus-mediated gene delivery, behavior, immunohistochemistry, tissue clearing and 3D imaging, image analysis, spatial
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in vitro models along with advanced 3D and 4D imaging technologies, we aim to illuminate key molecular and cellular mechanisms underlying human neural development and the pathogenesis of neurological
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computer vision and machine learning approaches to integrate ground-based imagery, remote sensing data, and lidar data for high-resolution flood detection and mapping. Develop and calibrate hydraulic flood
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buildings. All required qualifications must be documented on application materials. Required Qualifications: • PhD Degree in Neurosciences • At least 2 Years of experience • Record of peer reviewed
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
interpretable artificial intelligence to improve prediction accuracy while ensuring biological interpretability. The candidate will contribute to building computational frameworks that integrate diverse imaging
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synchrotron-based techniques to inform process development. The role requires a strong background in synchrotron characterization techniques, mainly three-dimensional imaging (microtomography and
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-coding elements offer important developmental/physiological functions, they also provide us with a unique angle to discover new biological/cellular processes in development and disease. Combining
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of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs
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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA
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advancement. The ideal candidate will have a PhD in computer science or related field utilizing computer science methods, strong expertise in medical image processing, registration and analysis and a long-term