Post-Doctoral Associate

Carnegie Mellon University; Pittsburgh (Allegheny County); On-site; USD 60,000 - 85,000; Full time

Job summary

A renowned academic institution in Pittsburgh is seeking two Post-Doctoral Associates to engage in computational social science projects. The successful candidates will explore online harms through agent-based modeling and social network analysis. Applicants should hold a PhD in a relevant field and possess programming skills in C and Python. This role offers the opportunity to work with extensive data and contribute to impactful research. Excellent academic writing skills are essential for producing research papers and presentations.

Qualifications

• Must have a PhD in a relevant 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 building and validating agent-based models.
• Excellent writing skills for academic purposes.

Responsibilities

• Work on agent-based simulation and empirical analysis projects.
• Develop and run virtual experiments.
• Analyze existing social media data and document results.
• Write papers with Dr. Carley and present results.

Skills

Programming in C

Programming in Python

Social network analysis

Basic statistics

Agent-based modeling

Education

PhD in STEM Field

Job description

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.

Equal Employment Opportunity Statement

Carnegie Mellon University is an equal opportunity employer. It does not discriminate in admission, employment, or administration of its programs or activities on the basis of race, color, national origin, sex, disability, age, sexual orientation, gender identity, pregnancy or related condition, family status, marital status, parental status, religion, ancestry, veteran status, or genetic information. Furthermore, Carnegie Mellon University does not discriminate and is required not to discriminate in violation of federal, state, or local laws or executive orders.