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work and, more specifically, how their activity can be modulated during embryonic development to shape anatomical structures. This is an issue important for evolution of morphological diversity across
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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. Specialized skills in molecular/cellular biology and animal model studies are needed for this position. Among the key duties of this position are the following: Treats and assesses mouse models
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approaches and research themes here: www.scilifelab.se/researchers/lisandro-milocco/ This project leverages the rise of data-driven dynamic modeling—from fluid dynamics to ecosystem studies—to uncover
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geographic patterns of dominant water level components over seasonal-to-interannual time scales. Develop methods for quantifying uncertainties in total water level estimations, considering coastal morphology
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for quantum information science, but many open questions remain regarding how to control the morphology and crystallinity of these host materials for exemplary performace as hosts for optically addressable spin
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, transplantation, and 2-photon Imaging in the mouse model of ischemic stroke. A major focus of the laboratory is to apply the long-term intravital single-cell tracking (LIST) under 2-photon microscopy to study the