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What is a computational science postdoc?

A Computational Science Postdoc is a researcher who has completed their Ph.D. and is engaged in advanced research that uses computational methods to solve scientific problems. These postdoctoral researchers often work in interdisciplinary teams, applying techniques like modeling, simulation, and data analysis to fields such as physics, biology, engineering, or environmental science. Their work aims to advance scientific understanding by leveraging high-performance computing and complex algorithms. Computational Science Postdocs may also contribute to software development, publish research findings, and collaborate with experimental scientists.

What are the key skills and qualifications needed to thrive as a computational science postdoc?

To thrive as a Computational Science Postdoc, you need a strong background in computational modeling, programming, quantitative analysis, and typically a PhD in a relevant scientific or engineering discipline. Familiarity with high-performance computing (HPC) environments, programming languages such as Python, C++, or MATLAB, and experience with specialized simulation software are essential. Excellent problem-solving abilities, collaboration, and clear scientific communication set outstanding candidates apart. These competencies are crucial for advancing research, tackling complex scientific challenges, and effectively disseminating findings in multidisciplinary teams.

What are some common challenges faced by computational science postdocs when working on interdisciplinary projects?

Computational Science Postdocs often collaborate with researchers from diverse fields such as physics, biology, or engineering. A common challenge is bridging gaps in domain-specific knowledge while ensuring computational methods are robust and accessible to all collaborators. Effective communication and adaptability are essential for translating complex scientific problems into computational models. Additionally, managing differing expectations and timelines across disciplines can require strong organizational skills and proactive project management.

What are popular job titles related to Computational Science Postdoc jobs?

For Computational Science Postdoc jobs, the most frequently searched job titles are:

Infographic showing various Computational Science Postdoc job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 75% Physical, 3% Hybrid, and 22% Remote job distribution.

PostDoctoral Associate in Computational Social Science

Boulder, CO • On-site

Complex Systems Society
See more jobs at Complex Systems Societyexternal

$60 - $80/hr

Other

Posted 7 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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