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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
, or a related field completed before the start date of the position Demonstrated experience with astronomical data analysis and software development Proficiency in Python programming Experience with large
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
, or a related field completed before the start date of the position Demonstrated experience with astronomical data analysis and software development Proficiency in Python programming Experience with large
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to decipher the regulatory code controlling gene expression in plants through the engineering and large-scale validation of synthetic promoters. Within the ERC-funded multiCODE project, we aim
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on advanced statistical methods for analysis of large-scale human genetic and neuroimaging data, to better understand how biological, psychological, and environmental factors contribute to severe mental and
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: A Ph.D. in biomedical informatics, computer science, information science, data science, (bio)-statistics, (applied
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world leader in genomics. The primary mission of the HGSC is actionable translational research across the full spectrum of human health and disease using large-scale genomic data to drive collaborative
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data and high-throughput, multi-dimensional -omic data to study neurodegeneration and diseases of the central nervous system, with an emphasis on Alzheimer disease, Parkinson’s disease, and other
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on collating and analyzing the large volumes of carbon cycle data gathered from the site to date, then preparing the resulting analyses for publication in scientific journals. Likely topics for papers include
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opportunities, outdoor recreation and Big Ten sporting events. Learn more about Iowa City and the Department of Internal Medicine by watching the video: https://medicine.uiowa.edu/internalmedicine/about-us/why
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modelling across different depths of human evolutionary history, building on methods published in Speidel et al, Nature 2025 and application to new large-scale modern and ancient genetic data. - Developing