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to identify the historical, structural, and contextual drivers of disease risk and inequity, and map pathways and interactions among determinants to inform disease mapping and modelling. The RA will lead the
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exhibit hallmarks of active matter. This PhD project aims to develop theoretical and computational active-matter models of early mouse embryogenesis that couple collective cell mechanics with gene
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the glycocalyx components. However, the physicochemical characteristics of these interactions and the spatial organisation of the glycocalyx remain poorly understood at the molecular level, as does how they shape
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in spatial analyses Excellent scientific writing skills, including ability to lead high quality multiple-authored journal papers in an efficient manner Strong ability to work independently and to
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solve research challenges and model development, as applicable. ● Contribute discrete components of a larger project under the general direction of a senior or principal researcher. ● Prepare complete
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University of California Agriculture and Natural Resources | Oakland, California | United States | about 2 months ago
appropriate test formulas and performs computations such as multiple and partial correlation coefficients, t-tests, Chi-square, ANCOVA, linear and logistic regression, multilevel modeling, spatial analyses
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-cell sequencing and spatial transcriptomics is preferred. This position will be an excellent opportunity to gain experience performing basic and translational research using patient-derived specimens and
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driving sex-specificity in tumorigenesis, organismal development, and spatial biology of the liver. To do so, we intersect large-scale genetic analysis utilizing experimental models with spatial and single
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for single-cell and spatial omics Deep learning and representation learning to model cellular states and interactions Explainable AI for biomarker discovery and patient stratification Cross-disease modeling
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population changes, and other demographic parameters (survival, fecundity, reproductive success, etc.). These integrated population models (IPMs) are increasingly used in ecology. They offer clear advantages