NYU College of Dentistry, Office of Educational Technology:

Research Assistant / Data Analyst position

The Office of Educational Technology (OET) partners with dental educators pursuing innovative approaches to improving teaching and learning practices, including the integration of educational technologies in their teaching and scholarship.. We conduct research on the impact of curricular design and disseminate that information to peer schools within NYU, and externally to other institutions and dental schools. 

OET  is currently engaged in multiple research projects on the scholarship of teaching and learning (SoTL). These collaborative research projects cover topics such as evaluating the integration of content in a team-taught course, adoption of a virtual reality simulation to prepare students for clinical work, analysis of student surveys in the context of a course in ethics and professionalism, and the integration of Generative AI tools into dental education curricula.

About the Position: Research Assistant / Data Analyst

Tasks: 

• As a Research Assistant / Data Analyst intern within OET, you will have the opportunity to work in various teaching and learning research projects. 

• Main focus will be on data analysis of quantitative and qualitative data sets. 

• The specific project to which the intern will contribute will be determined based on OET needs and the academic and professional background of the candidate.

Required Skills: 

• Working knowledge of quantitative software (e.g. R, Python, SPSS, etc.).

• Working knowledge of qualitative software (e.g. MAXQDA, etc.).

• Working knowledge of mixed methods research design methodologies and methods.

Desired Skills: 

• -Ability to review research study design and discuss any potential issues and solutions.

• Knowledge of Quantitative Bias Analysis (QBA)

Position Logistics

• Status of Role: Paid ($29.00/hr graduate student rate)

• Location: On-site at NYU College of Dentistry; option of hybrid placement

• Duration of Role: Spring 2025

To apply, please send your resume/CV and portfolio (or work samples) to Maaike Bouwmeester at mb262@nyu.edu and Chrissy Glaser at clg461@nyu.edu. 

• Additionally, applicants should submit a description of previous research projects they were involved in, including publications (if applicable). 

• Applications should also include a list of both quantitative and qualitative software tools which the applicant is familiar with and the level of expertise (low, medium, advanced) in using that software