Hire a QSS postdoctoral fellow

The Program in Quantitative Social Science has an active postdoctoral fellow program.  This program brings in bright and talented young scholars, who spend a year or two at Dartmouth following completion of their doctorates.  While on campus, QSS postdoctoral fellows work on their own research agendas and also collaborate with QSS-affiliated faculty members on joint projects.  


David Cottrell

David uses empirical and computational methods to explore political institutions in the United States, focusing on elections and representation. He is especially interested in how elections are affected by the location and manipulation of political boundaries. For example, David is involved in research that uses computer-automated districting algorithms to analyze the impact of gerrymandering on the partisan composition of Congress and on the lack of electoral competition in House elections. Furthermore, David's dissertation uses agent-based models and GIS methods to explore various ways in which geographically-defined political boundaries affect representation and policy administration.


Since coming to Dartmouth, David has been involved in a number of projects exploring ways in which elections distort representation. He has conducted research on disenfranchisement, measuring the extent to which African-Americans are removed from the electorate in thousands of legislative districts in the United States due to health and incarceration disparities. He has also analyzed claims of fraudulent voting in the 2016 presidential election to determine if voter fraud had a significant effect on Hillary Clinton's popular vote. And currently, David is working on a project that uses millions of voter check-in times during Florida's early voting period in 2012 to analyze how waiting in line to vote affects future electoral participation.

Jin Woo Kim

My research examines the effects of political (mis)information on public opinion. In an on-going research project, I use several survey experiments and an observational study to show that people account for the quality of evidence as they revise their opinions about highly polarized political issues. Methodologically, I’m interested in identifying communication effects based on real-world events such as political rumor diffusions and sudden shifts in news cycles. In a paper conditionally accepted for publication in the Quarterly Journal of Political Science, I highlight methodological challenges in identifying the effects of fake news, and suggest exploiting temporal overlap between rumor circulations and survey interviews can be a useful alternative, using an accidental and sudden spread of “Obama-is-a-Muslim” myths in September 2008 as an illustrative example.