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- Delft University of Technology (TU Delft); Published yesterday
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and imaging capabilities, and on applying THz (emission) microscopy to study 2D materials and 2D heterostructures. The microscope will use femtosecond lasers to generate and detect terahertz pulses
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person eager to contribute to cutting-edge biomedical imaging research and enhancing our understanding of the brain? The BrainEcho Lab within the Department of Neuroscience at Erasmus MC is looking for a
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Join our group to unlock ultrasound imaging inside bones! Job description Our group aims to unlock ultrasound imaging inside bones. Our ambition is to develop operator-independent approaches
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interdisciplinary research project in molecular ultrasound imaging using functionalized, monodisperse microbubbles. The project aims to understand how the acoustic response of microbubbles changes upon molecular
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neuroimaging frontier! Job description Understanding how the brain works is one of the most profound scientific challenges of our time. To that end, the development of new imaging methods is one of the most
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of manuscripts, the poetics of prayer, the function of images, and changes and continuities in relation to religious movements and the advent of print. PRAYER aims to yield an integrative understanding of the role
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language functions arise from large-scale brain networks and how these networks differ across individuals. The project combines advanced diffusion MRI tractography, functional imaging and multivariate
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security-oriented workflows. This includes designing methodologies that ensure traceability, robustness and bias mitigation in AI models, as well as creating prototype tools that demonstrate how transparent
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requirements should be implemented; design and propose architecture and operations concepts and propose recommendations on the most promising technologies that should be leveraged; prototype software
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of future Earth scenarios, for example “what if” scenarios; develop advanced embedding strategies and neural compression techniques to efficiently represent high-dimensional EO data for scalable learning and