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imaging using deep learning. You will study the water imbibition in hierarchically porous Si‑based material systems across multiple length and time scales. These systems can manipulate fluid transport
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-time employment. Starting date: 21.11.2025 Job description: PhD ? Multiscale Operando Super-Resolution Imaging of Water Imbibition Reference code: 923 Work location: Rostock Join the Cluster
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unified artificial intelligence (AI) model capable of segmenting 3D medical images from standard clinical scans and generating 3D meshes across multiple imaging modalities. The project will also investigate
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-matter interactions, via theory and simulations, to measure quantum dynamics in atoms and molecules. The project aims to explore new ideas for how quantum tomography, combining multiple measurements and
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works have shown that for embedding hierarchies, we should abandon Euclidean geometry altogether and operate in hyperbolic space [1]. Our lab has published multiple papers showing that hyperbolic deep
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Quantitative MRI is a PICNIK with Physics-Informed data Consistent Neural Implicit K-space representations. In this project, you will substantially improve quantitative magnetic resonance imaging
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Growing evidence suggests that hydroclimatic compound events - where multiple hazards occur simultaneously or sequentially - are becoming more frequent and severe in some regions of the UK (Visser
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University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations. Be You
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geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation
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Project Supervisor - Dr Jonathan Kirby The field of complex numbers is in many ways the most elegant and important example of a mathematical structure in model theory. It has been the prototype