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of a suitable candidate. The main topics of the group in the past few years were generative modeling, 3D reconstruction, image-editing, and deep learning using 3D data. More information about the
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supervision. Prepare, process, and ship specimens/samples accurately under well-defined requirements. Provide support for in silico 3D reconstructions of gross brain images and tissue and fluid-based
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. Experience in medical imaging, image processing, image reconstruction, machine learning and/or computer vision. Proficiency in mathematics, medical statistics, and 3D geometry. Proficiency in scientific and
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on existing methods, including a foundational model for mapping 2D mouse images to a canonical 3D mesh, with the goal of extending to full 3D reconstruction. This will enable inferring canonical 3D postures
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research to develop new mathematics and algorithms for analyzing complex data from DOE experimental facilities. Develop new mathematical algorithms targeting one or more focus areas: (1) 3D+ reconstruction
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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop 3D+t image reconstruction methods in a cell microscopy setting using image sequences as well as focus stacks
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researcher will work at the interface of root developmental biology, 3D modeling, network and graph theory, and data analysis, in close interaction with biologists, modelers, and computer scientists (INRAE
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of skin organoids requires 3D reconstruction to account for changes in tissue composition and structure. The appointment has an expected start date on or around April, 2026. The initial term of the position
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a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop 3D+t image reconstruction methods in a cell microscopy setting using image sequences
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programming (particularly IDEA) or image reconstruction Experience of computational modelling and simulatxion Knowledge of statistical and/or machine learning methods e.g. for 3D imaging data for applications