Research Assistant, Marsico Institute for Early Learning

Apply now Job no: 493146
Work type: Staff Part-Time
Location: Denver, CO
Categories: Research

The Marsico Institute for Early Learning is housed in the Morgridge College of Education (MCE) at the University of Denver. We have dedicated ourselves to improving learning environments and outcomes for children, birth to age 8. We identify the best in early learning research, practice, and policy, and we deliver that information at just the point it will be useful to academics, practitioners, policymakers, and parents — the people who can create and implement changes to improve the lives of young children. The quality of relationships and learning opportunities that young children experience can set the stage for what they will be able to accomplish throughout the rest of their lifetimes. 

Position Summary

The Marsico Institute is accepting applications for a part-time (10 hours/week on average) Research Assistant who will work on a new collaborative research project administered through the University of Denver, with collaborators at the University of Wyoming, to conduct re-analyses (and new interpretation and new analyses) of data from our extant LT Studies project (aka, Evaluating the Efficacy of Learning Trajectories in Early Mathematics). Visit our website to learn more:

Under the supervision and mentorship of Co-Investigator (Dr. Traci Kutaka) and Lead Statistician (Dr. Pavel Chernyavskiy), the Research Assistant will perform sophisticated statistical analyses of early mathematics intervention data, support on-going manuscript preparation and conference presentations, and will be responsible for developing and implementing best practices for data management, access, and dissemination. Opportunities for methodological research may naturally arise and the Research Assistant may be encouraged to pursue these, if their interests align with project goals.

This is a 1-year, grant-funded position, with possibility for renewal upon satisfactory performance. This is a non-benefited position not to exceed 1,000 hours in a calendar year. 

Essential Functions

  • Apply Bayesian statistical models to analyze child-level data collected during an early mathematics intervention.
  • Contribute to preparation and dissemination of peer-reviewed publications and conference presentations as co-author.
  • Develop strategies and best practices to manage and store project data, in compliance with federal requirements.

Knowledge, Skills and Abilities

  • Fluency and experience with statistical software such as: R, Python, Julia, Stan, etc. (please note that fluency with SPSS, STATA, and/or SAS will not be sufficient).
  • Facility with MS Office Suite/O365 programs, videotaping equipment, and basic features of virtual collaboration software.
  • Excellent communication skills and attention to detail.
  • Effective time management and organizational skills. 

Required Qualifications

  • Bachelor’s degree in Statistics, Biostatistics, Mathematics, Psychology, or a closely related field.
  • Experience conducting statistical analyses in R.
  • English language proficiency.

Preferred Qualifications

  • Experience with Bayesian statistics and/or categorical data analysis (e.g., logistic, Poisson, Ordinal regression models).
  • Experience writing co-authored manuscripts in a collaborative academic environment. 

Work Schedule

Part-time, schedule varies and is to be negotiated with project leads. 

Application Deadline

For best consideration, please submit your application materials by 4:00 p.m. (MST) on August 3, 2020. 

Special Instructions
Candidates must apply online through to be considered. Only applications submitted online will be accepted.

Hourly Range
The hourly range for the position is $20.00 - $27.00.

Please include the following documents with your application:

  1. Cover letter (no longer than one page)
  2. Curriculum Vitae
  3. A writing sample (e.g., final project for course, abstract for conference proposal, co-authored publication)

The University of Denver is committed to enhancing the diversity of its faculty and staff. We are an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment regardless of age, race, color, national origin, religion, sex, sexual orientation, gender identity, disability, military/ veteran status or any other status protected by law.

All offers of employment are based upon satisfactory completion of a criminal history background check.

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