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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 20 hours ago
statistics Familiarity with transport modeling Excellent verbal and written communication skills Experience with imaging and biochemical techniques such as PCR or Western blot Preferred Qualifications
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experience in image-based phenotyping, artificial intelligence applied to grapevine breeding, genome-wide association studies (GWAS), genomic selection (GS), and statistical analysis. Mandatory requirements
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The SDU Adaptive Intelligence Lab (ADIN Lab) (https://adinlab.github.io/ ) located under the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA
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Number req26754 Department Pharmacology and Toxicology Department Website Link https://www.pharmacy.arizona.edu/departments-directory/pharmacology-toxicology-department Location Tucson Campus Address
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Number req26751 Department Pharmacology and Toxicology Department Website Link https://www.pharmacy.arizona.edu/departments-directory/pharmacology-toxicology-department Location Tucson Campus Address
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SPECIFICS The Hamilton Lab (http://jillahamilton.com/index.html ) at The Pennsylvania State University is seeking to hire a Postdoctoral Scholar to contribute to funded research program aimed at studying
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, spatial and hydrologic modeling, statistical analysis, high-impact technical publishing, and collaborative proposal development. In support of NRRI’s mission to deliver applied science and sustainable
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of these interactions into soil and ecosystem models. Depending on the selected candidate, the research project can focus on statistical analysis of literature data, process-based modelling, or a combination of the two
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Qualifications · PhD or MD/PhD in neuroscience, molecular/cell biology, bioengineering, or a related field. · Demonstrated experience in extracellular vesicle exosome biology and advanced statistical analysis
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management databases; applying statistical methods to identify the main factors driving yield gaps; estimating productivity frontiers and crop responses to management practices; developing agronomic