Graduate Student Researcher – Social Science Reproduction Platform (Summer 2022)
BITSS is seeking a graduate student researcher (GSR) (up to 49% time) for Summer 2022 to support research activities as part of the Accelerating Computational Reproducibility (ACRe) project. The role will focus on conducting research on computational reproducibility, and co-creating guidance materials for the Social Science Reproduction Platform (SSRP).
The student will be responsible for:
- Reproducing five or more published research articles to test and suggest improvements to the SSRP and the accompanying Guide for Accelerating Computational Reproducibility (ACRe Guide).
- Cleaning and analyzing SSRP data and suggesting process improvements for data quality.
- Co-developing educational materials (e.g., FAQs) and refining existing guidance materials (e.g., reviewing the ACRe Guide for clarity and consistency with the SSRP).
- Prepare and apply for IRB approval for reproductions data analysis.
- Providing technical support to other graduate students conducting reproductions and instructors using the SSRP.
There may be an opportunity to extend this position through Fall 2022 depending on interest and availability.
Timeline:
Applications will be reviewed on a rolling basis until April 28, 2022.
Desired qualifications:
We are looking for a student with coursework or experience in economics, political science, psychology, public health, or another social science field, preferably having conducted a computational reproduction (or ‘replication’) of at least one published study. The ideal candidate has completed at least one year of coursework, is familiar with R, Github, SQL databases (optional), and has an interest in research transparency and reproducibility.
Salary step commensurate with experience at UC Berkeley.
How to apply:
Email abogdanoski@berkeley.edu with your CV, a brief statement of interest, and a link to a sample project (e.g., a GitHub/Bitbucket repo) or a writing sample, using the subject line: “BITSS SSRP GSR.”