PostDoctoral Associate in Computational Social Science

Complex Systems Society; Boulder (CO); On-site; USD 60,000 - 72,000; Full time

Job summary

University of Colorado Boulder is seeking a Postdoctoral Associate in Computational Social Science to join a project modeling the dynamics of the scientific ecosystem. The role involves developing new statistical and mathematical models and working across disciplines with experts in statistics, ecology, and data science.

The position aims to advance understanding of how research communities evolve, with emphasis on probabilistic modeling, causal inference, and data-driven analysis.

Qualifications

• Ph.D. (or equivalent) in a quantitative 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.

Responsibilities

• Model the dynamics of the scientific ecosystem using probabilistic and statistical methods.
• Develop new statistical and mathematical models of the causal forces shaping science and knowledge production.
• Collaborate across disciplines and communicate findings to diverse audiences.

Skills

Strong communication and presentation

Education

Ph.D. in quantitative field (applied math/CS/statistics/physics or related)

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 [e-mail] or Aaron Clauset with subject line "Science of Science Postdoc".