The Center for Statistics and Machine Learning is hiring a Computational Research Analyst to perform research on aggregated decision-making through rule systems with includes research into electoral mechanisms including the Electoral College, redistricting, and voting rules.
The Computational Research Analyst will develop computational analysis of redistricting and voting rules, toward the goal of performing analytics and scholarship relevant to identifying the performance characteristics and inefficiencies of U.S. democracy. The work will be made publicly available through peer-reviewed scientific scholarship as well as publicly available databases that may be of use to a variety of audiences.
A principal duty will be the updating and maintenance of a comprehensive resource for Congressional and legislative redistricting. The work will include dissemination and archival of codebooks, scripts, map content, and analytics. Other work includes the investigation of electoral rules such as ranked-choice voting and other modifications, with the goal of quantifying functional impacts. Translation to general audiences is part of the work and will produce content that is understandable to nontechnical readers. This comes in addition to other scholarship in scientific, statistical, and law journals.
This position is suitable for someone with graduate or postgraduate level competence in one or more relevant subject areas, including computational simulation, model testing, and geospatial analysis.
The term of this appointment is 1 year, with the possibility of renewal based upon satisfactory performance and funding.