Post-doctoral Position in Educational Measurement and Statistics – Tennessee Reading Research Center - UTK

University of Tennessee • Knoxville, TN

36d • $62,000 • Onsite

About The Position

The postdoctoral scholar will contribute to the TRRC’s goal of strengthening causal inferences while developing a range of skills in educational measurement and statistics. Current projects involve propensity score weighting, growth curve modeling, longitudinal data analysis, and meta-analysis. The work also might involve structural equation modeling (SEM), factor analysis, and item response theory. We are seeking to advance cutting edge methods that will incorporate AI. The position includes opportunities to produce peer-reviewed journal articles and contribute to the development of evidence-based educational practices. We seek a postdoctoral scholar to support the preparation and analysis of datasets. The scholar will have opportunities to contribute to the TRRC’s goal of strengthening causal inferences while developing a range of skills in educational measurement and statistics. Current projects involve propensity score weighting, growth curve modeling, longitudinal data analysis, and meta-analysis. The work also might involve structural equation modeling (SEM), factor analysis, and item response theory. We are seeking to advance cutting edge methods that will incorporate AI. The project is based in the College of Education, Health, and Human Sciences, a leading educational research institution, located in Knoxville, Tennessee. The position includes opportunities to produce peer-reviewed journal articles and contribute to the development of evidence-based educational practices. Depending upon the productivity of the scholar, there are possibilities for presenting at national conferences.

Requirements

• A completed doctoral degree (at least 10 days prior to the first day of work) in educational measurement and statistics, statistics, or a related field.
• Experience working with large and complex datasets.
• Experience conducting systematic reviews of the literature.
• Proficiency in statistical methods, particularly in modeling outcomes for multilevel and longitudinal data.
• Proficiency in using artificial intelligence (AI) in advanced analyses.
• Advanced knowledge of R or other statistical software (e.g., Mplus, Python).
• Strong verbal and written communication skills, with a proven ability to convey complex statistical concepts to diverse audiences.
• Experience working independently.

Nice To Haves

• Experience with all phases of experimental research (e.g., power analyses, pre-analysis planning, harmonizing data, analyzing outcomes, analyzing moderators, sensitivity analyses, intent-to-treat analyses, etc.).
• Expertise with educational measurement development and validation, including multilevel item response theory (IRT) modeling, factor analysis, and structural equation modeling (SEM).
• A record of scholarly publications and presentations.

Responsibilities

• Clean and harmonize complex educational datasets.
• Conduct analyses to determine the effectiveness of interventions using techniques such as propensity score weighting, multilevel modeling, and meta-analysis.
• Conduct analyses to validate educational assessments using techniques such as structural equation modeling (SEM), factor analysis, and item response theory.
• Apply AI in advanced analyses.
• Support data management on externally funded grants and contracts.
• Collaborate on peer-reviewed journal articles.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree