Postdoctoral Researcher in Computational Social Science
Workplace: Linköping, Sverige
Expires: September 30, 2025
Postdoctoral position within the Excellence Centre in Computational Social Science (SweCSS) at Linköping University, focusing on research combining social science theories with computational methods. The role involves conducting research primarily, with possible teaching duties up to 20%.
Main requirements:
  • PhD or equivalent foreign degree completed by the time of employment decision.
  • PhD in computer science, statistics, sociology, economics, political science, or related fields relevant to computational social science.
  • Demonstrated expertise in combining social science theory with computationally intensive methods to understand societal phenomena.
  • Research plan showing potential for groundbreaking research within computational social science (CSS).
  • Research plan must clearly involve both the Institute for Analytical Sociology (IAS) and the Department of Computer and Information Science (IDA).
  • Good collaboration skills and interest in interdisciplinary research across institutional boundaries.
  • Proficiency in English, both spoken and written.
Responsibilities:
  • Conduct research within the framework of the Swedish Excellence Centre for Computational Social Science (SweCSS).
  • Potentially teach up to 20% of working time.
  • Collaborate across departments (IAS and IDA) and disciplines.
  • Adapt roles and responsibilities according to research project needs and team competencies.
Required hard skills:
  • PhD in relevant field (computer science, statistics, sociology, economics, political science, or similar).
  • Expertise in combining social science theories with computational methods.
  • Competence in programming and data analysis.
  • Experience applying computationally intensive methods such as data-driven text analysis, network analysis, machine learning, large language models, causal inference, and agent-based modeling.
  • Ability to collect, curate, and analyze large digital datasets relevant to social sciences.
Recommended hard skills:
  • Experience coding and teaching programming languages such as R and Python.
  • Experience working across institutional boundaries.
  • Participation in interdisciplinary researcher networks.
  • Representation in scientific organizations.
  • Secured interdisciplinary research funding.
Soft skills:
  • Collaboration skills.
  • Flexibility and creativity.
  • Interdisciplinary communication and teamwork.
  • Ability to shift roles and responsibilities as dictated by research projects.
  • Openness to cross disciplinary boundaries.
Coding languages:
  • R
  • Python
Frameworks:
  • Data-driven text analysis
  • Network analysis
  • Machine learning
  • Large language models
  • Agent-based modeling
Natural languages:
  • English (Proficient)
Cultural skills:
  • Interdisciplinary collaboration
  • International research cooperation
  • Working across institutional boundaries
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