Postdoc Quantifying Gender Inequality in Visual Art

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University of Amsterdam (UvA)

Hybrid
  • Career category: Research/ Data analysis
  • Job type: PhD
  • Experience level: Not specified
  • Organisation type: Research
  • Remote option: Hybrid
  • Right to work requirements: Anyone can apply
  • Remuneration: €4,728 EUR-€6,433 EUR / monthly
  • Work schedule: Full-time
  • Length of contract: Temporary/ Fixed-term
  • Deadline: 23/02/2026
  • Location: Netherlands
Movement building
Are you passionate about art, gender equality, and data-driven research? Join the HERAtlas project to uncover the "invisible" women of art history. We are looking for a Postdoc to combine data science, psychology, and history to reveal the structural barriers behind gender inequality in the creative industries and translate these insights into public storytelling.

Working at the UvA
Decode the Data Behind the Gender Gap in Art
You will be based in the Department of Psychology, working as part of a unique interdisciplinary team spanning Psychology, Informatics, and Digital History. By applying computational social science or computational humanities methods to large-scale longitudinal datasets, you will model how economic, educational, and political drivers have shaped the visibility of women artists over centuries. You will not only analyze these patterns but also collaborate with design partner Studio Bertels to translate your findings into public showcases and policy tools. We are looking for a researcher who is comfortable with advanced data analysis and eager to apply those skills to complex cultural questions.

What are you going to do
  • Construct and analyze longitudinal datasets of inclusion indicators to contextualize art collections.
  • Develop and test statistical models to determine how structural societal shifts influence women’s artistic visibility over time.
  • Translate statistical findings into narratives by collaborating with designers to create "what-if" simulations and visualizations for public-facing events.
  • Co-author scientific publications and present findings at interdisciplinary conferences alongside a team of psychologists, historians, and computer scientists.

What do you have to offer
  • Must-have: You have completed a PhD in psychology, computational social science, computational humanities, data science, AI, or a closely related quantitative field.
  • Must-have: You can independently and confidently analyze quantitative data and you can write reproducible code (for example, in R or Python).
  • Good-to-have: You have experience working with large-scale text or visual data, or datasets related to history or culture.
  • You tackle complex data challenges with curiosity and are driven to understand the why behind patterns.
  • You enjoy bridging the gap between technical analysis and social impact, translating complex results into clear stories for non-technical stakeholders

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