POSTDOCTORAL ASSOCIATE, Political Science, to join a National Science Foundation-funded computational social science research project with Professor In Song Kim. The project focuses on using computational methods to examine special interest group politics and trade politics in the U.S. Responsibilities include analyzing lobbying and campaign donation data and developing/maintaining a large-scale money-in politics database. The team is currently developing novel computational methods for social science research such as community detection and graphical neural network methods to infer political networks; and natural language processing (NLP) methods to investigate congressional bill writing and entity disambiguation. The position offers an opportunity to engage in independent research projects according to the candidate's substantive research interests/background.
REQUIRED: Ph.D. (or an anticipated Ph.D. completion by May 2023) in and research experience with computational social science, political science, computer science, economics, or a related field; ability to work independently with general supervision and as part of a team; experience working with remote servers (Linux CLI, AWS); Python/Git development skills; and knowledge of SQL and relational database modeling.
PREFERRED: experience with data-driven social sciences, experience with large-scale data handling, and knowledge of Postgres. Job #21632
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