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Carnegie Mellon University

Post-Doctoral Associate

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Job Description

Carnegie Mellon University:
School of Computer Science:
Software and Societal Systems Location:
Pittsburgh, PA Description:
The Software and Societal Systems Department, in the School of Computer Science, at Carnegie Mellon University is looking to hire two Post-Doctoral Associate who are interested in applying computational social science approaches to the study of online harms. Ongoing projects in which these postdocs will be involved include - assessment of influence campaigns and measuring their impact, meme analysis, online threat detection, assessment of techniques for countering information maneuvers, differences in online harms and influence campaigns across countries, geo-spatial differences in online harms. Successful applicants will need experience in either or both agent-based modeling and social network analysis/network science. The ideal candidate should be able to program in C or C and have experience working with tera-bytes of data. Preference for those who can also program in Python and know standard network analysis techniques and metrics such as community detection and centralities. Prefernce for those with experience in geo-spatial analysis, assessment of images, or assessment of memes. Preference for those with experience working with large scale data, millions of actors and messages. Successful candidates will work on at least two related agent-based simulation and empirical analysis projects, develop and run virtual experiments, analyze existing social media data, document results, write papers with Dr. Carley and possibly relevant PhD students, and present those results in the IDeaS conference. Candidates should be interested in studying behavior where the media posts are in non-English languages i.e. Chinese and Russian.
Qualifications:
Must have a PhD in STEM Field (including computational or mathematical social science). Ability to program in C and Python. Must know basic statistics. Experience in social network analysis. Experience using, building, validating and working generally with ABM's. Excellent writing skills for academic writing.