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Field
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demonstrated independent thinking and problem-solving abilities. Experience using large databases is preferred, and genetic data analysis skills are desirable. Required Qualifications PhD or MD in Public Health
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the Project HOPE 1000 pregnancy cohort, a large, longitudinal study based in Durham, North Carolina, to investigate how prenatal and early-life environmental exposures influence immune-related outcomes during
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software development, and has leading roles in the ATLAS High Luminosity Large-Hadron Collider (HL-LHC) upgrade (Silicon Strip detector, Liquid Argon calorimeter, and Trigger & Data Acquisition). The group
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experiment at CERN in Geneva, Switzerland. The Omega Group has major responsibilities in detector operations and software development, and has leading roles in the ATLAS High Luminosity Large-Hadron Collider
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
requested or required to support the work of the research project. Minimum Education and Experience Requirements PhD in one of these fields: Computer Science, Data Science, Biomedical Informatics
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analysis of large data sets Prior experience in signal transduction research Knowledge, Skills and Abilities: PhD level knowledge and understanding of basic cellular and molecular biology Expertise in cell
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-Intensive Engineering and Science (part of the new Data Science and AI center), and at the National Radio Astronomy Observatory. Required qualifications are: PhD in Astronomy, Astrophysics, Physics, or a
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future funding. Required Education and Experience Appropriate PhD in a related field Preferred Qualifications Willingness to work with large animal models Experience with tissue culture and primary cell
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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing
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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science