Research Assistant Position/AY 2018-2019
Professor Rachel Stern, Berkeley Law
The Project. Since 2014, over 60 million Chinese judicial decisions have been placed online as a result of a new national policy mandating the online release of most court documents. The RA will assist in querying and analyzing a database of Chinese court decisions as part of a multi-year effort that brings together scholars at Berkeley, UCSD, and Columbia to analyze this deluge of new information. This massive expansion in the public record of court activity promises to re-shape our understanding of Chinese law and, beyond China, of authoritarian legality. This is an unusual opportunity to work with a large and unique dataset that very few scholars have yet had the opportunity to study.
Qualifications. I’m looking for Berkeley students (graduate/undergraduate) with a background in data science, who have taken classes related to natural language processing and machine learning. You should be able to work in SQL and Python, and have a strong interest in learning about law and/or social science research. Knowledge of R and a working knowledge of Chinese would also be a plus. Because this is a multi-institution collaborative project, the RA would also be responsible for working with technical leads at UCSD and Columbia.
Pay: Berkeley student assistant rates, depending on experience. There may also be opportunities to co-author research papers, and to travel to San Diego and New York for meetings of the bigger research team.
Hours and duration: 8-10 hours a week through mid-May 2019. Preference will be given to students who are available to keep working through the summer, or during next academic year.
Expectations for RAs: RAs are expected to turn attend weekly meetings of the Berkeley-based research team, and respond promptly to email between Monday and Friday.
How to Apply: Send a resume, informal transcript and short email describing why you are interested in the position to Rachel Stern at rstern@law.berkeley.edu. I will review applications and schedule follow-up interviews with an eye towards completing hiring as soon as possible.