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innovative research, UTA is designated as a Carnegie R-1 “Very High Research Activity” institution. UTA ranks No. 4 nationally in Military Times’ annual “Best for Vets: Colleges” list and is among the top 30
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experience in analyzing clinical trials data. The applicant must have excellent communication skills (verbal and written), strong programming skills in R with proficiency in UNIX/Linux system. For the meta
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. Prerequisites Doctoral degree with quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, including proficiency in proving asymptotic properties. - Ability to implement, test, and document statistical methods in R. - Ability to analyze real-world datasets. - Ability to write and publish scientific
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skills in R and/or python Experience with iPSC and/or cell culturing What we offer As part of the VIB-UAntwerp Center for Molecular Neurology and VIB , the applicant will benefit from established
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employment The position is for a 2-year period starting 1 August 2025. Job description The post doc will join Kasper R. Andersen’s research group working on structural and functional analysis of plant
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with STATA, R, Python or related statistical software. GIS expertise is ideal. Application Process Please submit an online application and attach the following documents: Short statement of research
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skills in R and/or python Experience with iPSC and/or cell culturing What we offer As part of the VIB-UAntwerp Center for Molecular Neurology and VIB , the applicant will benefit from established
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Founded in 1848, the University of Mississippi (UM), affectionately known to alumni, students and friends as Ole Miss, is Mississippi's flagship university. Included in the elite group of R-1
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biochemistry techniques in weed science is essential Ability to use R statistical program or python is required Expectation of experience in computational tools and unix for analyzing and visualizing large data