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advanced image segmentation methods to join our imaging research group and project “Natural Heritage 3D”. This collaborative project between Visual Computing @ DTU Compute, DTU Physics, Copenhagen
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Grafing bei München, Bayern | Germany | about 2 months ago
generative AI models that transform unlabeled or 3D tissue images into realistic virtual stains, such as synthetic H&E images or biomarker maps Develop and implement image processing, data preparation, and
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2D/3D/4D image parsing, segmentation, and building robust computer-aided detection systems Proficiency with modern deep learning frameworks (PyTorch, TensorFlow) and related tooling Demonstrated
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der Länder, TV-L ), pay grade E13. Duties/responsibilities: Development of advanced 3D human in vitro tissue models using biofabrication and biomaterial-based approaches Establishment and optimisation
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking for a Research Assistant (Crop Experiments and Sensing
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interested in candidates who understand animation as both a technical and artistic practice that can intersect with drawing, sequential art, illustration, painting, digital image-making, 3D practice
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particularly interested in static and dynamic 3D reconstruction, semantic scene understanding, and generative models for photo-realistic image / video synthesis. Overall, the main focus is on high
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 10 hours ago
the exact research topic depends on the background of a suitable candidate. The main topics of the group in the past few years were generative modeling, 3D reconstruction, image-editing, and deep
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Sciences / David Geffen School Of Medicine / UCLA Position overview Position title: Abdominal Imaging Fellow/Health Sciences Clinical Instructor Salary range: The posted UC salary scales ( https
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networks and graph-based neural operators for fast estimation of 3D coronary hemodynamics (velocity, pressure, and wall shear stress fields); design computational pipelines that integrate image-based