41 modelling-complexity-geocomputation Fellowship positions at University of Michigan
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search of an exceptional postdoctoral fellow to join the research team. The laboratory is situated in the heart of Michigan Medicine at the North Campus Research Complex in a newly renovated laboratory
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models. The Sutton Lab is housed within the Michigan Neuroscience Institute (https://medicine.umich.edu/dept/michigan-neuroscience-institute ) in the Interdisciplinary Taubman Biomedical Sciences Research
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novel inhibitory/degrader drugs in preclinical models. The individual should be familiar with routine molecular biology techniques and have an educational background in biomedical sciences or related
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develop AI models to predict and study the tumor evolution and lineages using the multiomic measurements from both bulk, single-cell, and spatial technologies. The lab emphasizes understanding
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signal processing models to analyze waveforms generated by traditional patient monitors and a novel wearable sensor and build a decision support tool to guide CPR Participate in the user interface and
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interdisciplinary lab focuses on investigating genetic and epigenetic changes in traumatic brain injury. The successful candidate will work on animal models of brain injuries and apply cutting-edge spatial multi-omic
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resistance, utilizing human and murine cells, orthotopic models, and Genetically Engineered Mouse Models (GEMMs). We are seeking a motivated and hard-working scientist with strong project leadership and
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; patient care, education and research that together enhance our contribution to society. Why Join Michigan Medicine? Michigan Medicine is one of the largest health care complexes in the world and has been
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recruiting a post-doctoral researcher to develop computational models to study the spatial organization and microenvironment interactions in tumors using spatial multiomic data. The lab focuses on mathematical
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-driven (i.e., prostate and breast) cancers. They will also assess druggability of these genes using novel inhibitory/degrader drugs in preclinical models. The individual should be familiar with routine