Research Fellow

Deadline to apply: First consideration will be given to those who apply by Monday, December 9, 2024, but will continue to be accepted until the positions are filled. Ideal candidates can start on or before Monday, January 6, 2025.
Location: 317 Maynard St., Ann, Arbor, MI 48104 (hyrbid)
Pay Rate: Master’s $20/hr, Doctoral $23/hr
Job Duration: 10 – 15 hours/week in Winter 2025, with the possibility of extending to Spring/Summer 2025
Hiring Manager: Becky Matz ([email protected])

Who we’re looking for:

In partnership with colleagues from the College of Engineering, the Research & Analytics team at the Center for Academic Innovation (CAI) seeks to hire two independent, creative, detail-oriented, and reliable graduate students as Research Fellows to support research on a digital team support tool called Tandem. With appropriate support, the Fellows will be responsible for a scoped quantitative education research project that relies on existing Tandem data. One example project is developing a default rule set (based on Tandem survey items) for team formation that supports equitable team behaviors and outcomes. Another example project is evaluating the relationship between teammates’ responses to survey items collected in the middle versus at the end of the semester. The Fellows should be familiar with at least one modern computational language or program that supports statistical analysis (e.g., R, Python, Stata, SPSS, etc.) and some combination of education research, learning analytics, statistical analysis, and data management. We have a goal that all Fellows present the results of their work at an internal conference; presenting at external-to-UM conferences and writing an article for publication may be options as well.

What You’ll Do:

• Organize, clean, manipulate, analyze, interpret, and articulate findings based on Tandem data and closely related data sources
• Produce effective visualizations
• Prepare and present reports and findings to collaborators and colleagues

Experience and Skills You’ll Gain

• Experience with interpreting and characterizing educational data
• Experience with survey research and handling missing data
• Experience creating clear and accessible data visualizations
• Knowledge of, and experience with, quantitative inquiry and various statistical analysis techniques such as logistic regression, analyses of variance, factor analyses, and linear and hierarchical modeling

Student Qualifications:

• Currently pursuing a master’s degree or PhD in education, information, data science, or a related field
• Familiarity with a modern computational language or program for analysis (e.g., R, Python, Stata, SPSS, etc.)
• Demonstrated ability to be self-directed and work independently and as part of a rapidly changing, multidisciplinary, multicultural, and collaborative environment
• Ability to communicate the results of data analyses to non-technical audiences

How to apply

Complete this Student Fellowship Application which includes uploading your cover letter and resume (or CV).