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Postdoc in Computational Social Science

6 Feb 2023

Job Information

GESIS - Leibniz-Institut für Sozialwissenschaften
Research Field
Researcher Profile
Established Researcher (R3)
Application Deadline
Type of Contract
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Hours Per Week
Offer Starting Date
Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme
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Is the Job related to staff position within a Research Infrastructure?

Offer Description

GESIS – Leibniz-Institute for the Social Sciences is an internationally active research institute, funded by federal and state governments and member of the Leibniz Association.

Starting on 01.04.2023, our Department Computational Social Science (CSS)Team Transparent Social Analytics located in Cologne, is looking for a


Postdoc in Computational Social Science

(Salary group 13 TV-L, working time 100%, initially for 4 years with possible tenure)


GESIS is strategically realigning and growing: Digital behavioral data will be a focus of our activities in the future. The goal across all GESIS departments is to build new tools and infrastructures to support the collection, processing, analysis and archiving of digital behavioral data and to conduct research on current societally relevant questions with new methods and new types of data.

The interdisciplinary and internationally constituted department Computational Social Science (CSS) is dedicated to the study of socio-cultural phenomena and digital society. For this purpose, we are using new approaches to data collection (e.g., web data collection, web tracking, smartphone apps) as well as different types of methods for analysis (e.g., machine learning, network analysis, text and data mining), and standards (reproducible  workflows).

The advertised position will be part of a new team with a focus on Transparent Analytics and Open Science, in particular on the establishment of a service infrastructure for innovative open science services in the context of digital behavioral data.


Your tasks will be:

  • Contributing to an interdisciplinary team, which focuses on the establishment of a service infrastructure for innovative open science services in the context of digital behavioral data
  • Making computational methods accessible, re-usable and comprehensible to social scientists and evaluating methods based on different quality criteria
  • Conducting application-based research in the area of computational social science
  • Acquisition of external funding with a focus on research and research-based services
  • Very good command of written and spoken English

Your profile:

  • Completed doctoral degree in a field relevant for computational social science, for example applied computer science, statistics, physics, political science, communication science, psychology, sociology or related disciplines
  • Well-defined research profile in computational social science using and developing relevant methods such as network analysis, machine learning, natural language processing, and text/data mining
  • Expertise in data analysis using R and/or Python as well as experience with Jupyter Notebooks/Rmarkdown is a plus
  • Visible activities related to open science (open methodology, open source or open access) e.g. by publishing methods/code on established platforms, development of tools or method-focused training activities

Our Benefits:

  • An international and interdisciplinary working environment with a friendly and collegial atmosphere
  • Flexible working hours and the possibility of up to 60% mobile working within Germany
  • Generous support for your pension provision as a direct insurance policy
  • Very good conditions for reconciling work and family life, e.g. subsidies for childcare for children who have not yet attained the age of compulsory schooling
  • Holistic company health management and discounted participation in the university's sports programme
  • Promotion of your skills through further training measures


For further information concerning the position and the CSS department, please contact Dr. David Schoch via e-mail. If you have questions about the application process, please contact Franca Tosetti via e-mail.



Please apply via our Online-application portal until 27.02.2023.

Our reference number is: CSS-84.


Research Field
Education Level
PhD or equivalent

Additional Information

Work Location(s)

Number of offers available
GESIS - Leibniz-Institut für Sozialwissenschaften
Postal Code
Unter Sachsenhausen 6-8