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in qualitative and quantitative research methods and data analysis tools, such as R, SPSS, Stata, MAXQDA, and Nvivo. Aid in the analysis of data to derive insights into best practices for practitioners
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, analysis, architecting, and design is desirable. Smart, Connected, and Healthy Communities: Smart Integrative Energy Systems The Ezra Systems Post-Doctoral Associate on the track of Smart Integrative Energy
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analysis to detector operations and high luminosity detector upgrades (HL-LHC) of the pixel forward detector and the track trigger. The successful candidate will actively engage in searches for long-lived
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a year with the opportunity to extend based on performance. Anticipated Division of Time: 80% Research, 15% Data Analysis, 5% Writing Requirements: Ph.D. in Biochemistry, Chemistry, Molecular Biology
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Associate are as follows with time allocation: Model development and evaluation (70%) - Analysis and quantification of methane data from chambers and predictions from the CNCPS, sensitivity around inputs
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members and be responsible for contributing to: Manuscripts, reports, abstracts for conferences, grant proposals Data analysis and pipeline development Technology-based solutions for advancing population
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to: Manuscripts, reports, abstracts for conferences, grant proposals Data analysis and pipeline development Technology-based solutions for advancing population health To be eligible, candidates must: Have received
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from doctoral work is required. Experience in cancer research and bioinformatics analysis is desirable but not essential. Supervision Exercised None To apply: Please apply via Academic Jobs Online (https
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on cancer or metabolism-related diseases like obesity and diabetes should not apply). Evidence of publication from doctoral work is required. Experience in cancer research and bioinformatics analysis is
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of the CNCPS. Primary duties: The specific functions of this Postdoctoral Associate are as follows with time allocation: • Model development and evaluation (70%) - Analysis and quantification of methane data