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Phd Computational Social Science Jobs (NOW HIRING)

Interos Inc.

Lead Computational Social Scientist

Role: Lead Computational Social Scientist   About interos.ai:  interos.ai is the standard for ... PhD in political science, economics, or other social or behavioral science, actuarial science, or ...

Protagonist

Computational Social Scientist

Washington, DC · On-site

$70K - $102K/yr

Our work lives at the intersection of data science and social science: we pair computational techniques with an understanding of the social, political, and information dynamics behind the data. This ...

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As of Sep 11, 2026, the average hourly pay for phd computational social science in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 per hour, depending on experience, location, and employer.

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Infographic showing various Phd Computational Social Science job openings in the United States as of July 2026, with employment types broken down into 68% Full Time, 31% Part Time, and 1% Contract. Highlights an 65% Physical, 2% Hybrid, and 33% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

PostDoctoral Associate in Computational Social Science

Boulder, CO • On-site

Complex Systems Society
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Posted 10 days ago

Job description

PostDoctoral Associate in Computational Social Science

PostDoctoral Associate in Computational Social Science at University of Colorado, USA

The research groups of Professors Daniel Larremore and Aaron Clauset at the University of Colorado Boulder are seeking exceptional candidates for a postdoctoral research associate, to work on an innovative project modeling the dynamics of the scientific ecosystem. This project will combine theories and methods from Computational Social Science, Statistical Inference, Dynamical Systems, Ecology, and Evolutionary Biology to better understand the way that science and knowledge production work.

The initial term of the position is one year, with the possibility of up to two renewals, and will begin as early as January 2020 and no later than August 2020.

Ideal candidates will have a strong mathematical, statistical, and computing background; a strong track record of innovative research and publications in selective venues; and expertise in computational social science, ecology, and/or data science. The project will focus on developing new statistical and mathematical models of the causal forces that shape the structure and dynamics of the scientific workforce, spanning individual researchers and their careers, competition among departmental units, and the evolution of entire fields. Our main tools are probabilistic models, random walks, causal inference, and statistical algorithms, coupled with ideas from statistical physics, social science, and ecology. Familiarity with one or more of these techniques is desirable, but is not a requirement.

Qualifications
  • A Ph.D. (or equivalent) in Applied Mathematics, Computer Science, Statistics, or Physics, or in a quantitative branch of Ecology, Sociology, or Computational Social Science, or in a similar field, conferred no later than August 2020
  • Education or training in statistics, data analysis, and programming
  • Strong communication and presentation skills
  • A commitment to working in an interdisciplinary and collaborative environment.

For additional information, please contact Dan Larremore daniel.larremore@colorado.edu or Aaron Clauset with subject line "Science of Science Postdoc".

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