949 development-"https:"-"https:"-"https:"-"https:" "https:" Postdoctoral research jobs in United States
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development ( https://rupress.org/jcb/article/220/11/e202103080/212704/ ) or regeneration ( https://www.science.org/doi/10.1126/sciadv.adi7840 ). To address these questions, we use mouse and cell
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and optical imaging (Leung Research Group) The Leung Research Group (https://sites.google.com/view/LeungGroup) in the Department of Intelligent Systems Engineering at the Luddy School of Informatics
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proteins and related lncRNAs in regulating oncogene expression under the three-dimensional chromatin niche; and (3) development of novel tumor models, new methods, and advanced technologies to
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. Ondersma (https://publichealth.msu.edu/flint-research/flint-public-health-research/steven-ondersma-phd), Dr. Claire Margerison (https://epibio.msu.edu/research/mrg/), and Community MPI Athena McKay (https
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interests regarding mechanisms of T cell development, activation and memory generation in the context of acute and chronic viral infections. Current projects include 1) determining the impact of
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vivo perturbational screening. We have developed single-cell CRISPR technologies that enable dozens of molecular factors to be screened in vivo during development and disease, accelerating the
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Classification Title: Postdoctoral Research Associate - The Neurocognitive and Behavioral Development Laboratory Classification Minimum Requirements: Ph.D. in Cognitive Neuroscience, Clinical
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development mentoring experiences. Compensation and Benefits: Compensation will be at or above the University minimum of $44,400 annually ($3,700/month) https://postdocs.yale.edu/postgrads/being-a
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implications. For more information regarding benefits, visit https://grants.nih.gov/grants/policy/nihgps/html5/section_11/11.3.8_allowable_and_unallowable_costs.htm https://grants.nih.gov/grants/policy
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are seeking highly motivated postdoctoral researchers in biomedical informatics and data science to work on projects focused on the development of biomedical blockchain, clinical predictive models