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lung fibrosis. The ideal candidate will independently perform studies utilizing established in vitro, ex vivo and in vivo preclinical models and will have the opportunity to develop and refine novel
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analysis and statistical modeling. Experience working with large, complex, and multi-dimensional datasets. Experience with spatial analysis and geospatial data integration, including use of GIS tools (e.g
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extremely valuable. Good expertise in micro-econometric modelling would also be desirable, as would an interest in – and experience working on – low and middle income countries. Your role The Research
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are of interest. The primary objective of this PhD project is to develop adaptive statistical models for marked spatial and spatio-temporal point processes. Many real-world systems exhibit substantial spatial
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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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nécessaire pour suivre les bilans des gaz à effet de serre, la production de biomasse et les rendements agricoles. À ce jour, la plupart des méthodes permettant d'estimer spatialement la GPP s'appuient soit
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, progression, and therapeutic response. This research is fundamental to advancing our knowledge of cancer and improving patient outcomes. See further information at the lab webpage: https://odin.mdacc.tmc.edu
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Shankland Lab group to analyze high-throughput data sets related to the kidney in the settings of pre-clinical models of disease and aging. Specifically, the lab utilizes transcriptional profiling approaches
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machine learning (ML) approaches offer a powerful framework for modeling complex catalytic materials with near ab initio accuracy while enabling simulations at significantly larger spatial and temporal
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the molecular signatures of proteostasis loss and identify early markers of proteostatic failure. The role combines wet-lab spatial biology with computational approaches. You will work across models and scales