Position Summary
The School of Engineering Education at Purdue University is seeking a postdoctoral researcher to investigate how the use of visualization and simulation tools impacts undergraduate students' understanding and attitudes in topics related to semiconductor physics. The researcher will use statistical methods such as multilevel models and multivariate analysis of variance to take into account key variables and covariates to study the impact on students’ outcomes. The researcher will use mixed methods, including data from knowledge tests, attitudinal surveys, and focus groups to investigate how the tools function and how they can be improved. The researcher will also examine the measurement properties of the tests and surveys to ensure they measure the constructs as intended and provide recommendations for improvement. Responsibilities include data analysis (quantitative and qualitative), item analysis, assisting with focus groups, and dissemination of research findings, including conference presentations and preparing manuscripts for publication in academic journals. The researcher will collaborate on an interdisciplinary team with engineering education researchers and researchers in semiconductor physics. The position is anticipated to last for 2 years pending availability of funding; an extension is possible based on funding and project needs.
Interested candidates should submit an application containing a cover letter detailing their qualifications and interest in the position and CV. Review of applications will begin immediately and continue until the position is filled with an anticipated start date of August 2025.
Education and Experience
Ideal candidates will have a Ph.D. in engineering education, social sciences, statistics, education, or a related field. Experience with publishing and presenting research is required.
Skills
Must be a self-starter with strong interpersonal, communication, organizational, problem-solving, and statistical software skills (e.g., R). Strong background in quantitative data analysis and research methodology is preferred. Ideal candidates will also have experience in psychometrics and mixed methods research.
FLSA Status
Exempt