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conservation, and aid authentication. Modern scientific imaging techniques now generate large volumes of complex data that can reveal new insights for art historians, conservators, and the broader public. Among
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in policy and decision-making. In this PhD, you will contribute to a new generation of spatially explicit models and assessments that capture these feedbacks across spatial and temporal scales
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scenario; Develop a novel self-calibrating, heterogeneous distributed platform capable of providing the necessary sensing, transport, compute and data aggregation capabilities on demand. Consider how partial
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project where we will develop a next-generation diffusion MRI acquisition to map the organization and properties of fibers in the human brain cortex, both post-mortem and in-vivo. You will: Evaluate
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of tomographic imaging techniques to capture oil/water distributions in a 3D geometry. In the second half, we will use these techniques to study the flow and stability of an emulsion through a constriction
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and analysing general Computer Vision methods, using real-world image data as a challenging experimental setting. Research focus The PhD will address open research questions in Computer Vision related
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with next generation high-tech systems? The main challenge lies in the reliable operation of the entire system, where many interconnected modules affect each other. In this project, you will be designing
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. Improve georeferencing and interpretation of InSAR point and distributed scatterers, linking results to buildings, parcels, and land-use information. Disentangle contributing deformation mechanisms
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ideally suited for continuous interferometry. You will design and construct a compact rotation sensor using a rubidium atomic beam generated by a 2D-MOT, achieving mean velocities around 20 m/s and enabling