Doctoral Researcher in spatial data management (SDC-36)

Descripción del puesto

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 January 1, 2027, our Department Survey Data Curation , Team Survey Data Augmentation, located in Cologne , is looking for a Doctoral Researcher in spatial data management (Salary group 13 TV-L, working time 75 %, limited to 3 years) The department “ Survey Data Curation “ processes and prepares social science research data across a diverse range of data types to support sociological and political science research, especially in comparative perspectives across space and time. The curated data include long-running national (e.g., ALLBUS, GLES) and international (e.g., ISSP, CSES) survey programs, which are documented and curated to the highest quality standards, but also research data products derived from or connected to these surveys, such as geo referencing services or trend files. “Electoral Spaces” is a project of our team Survey Data Augmentation that develops a research data infrastructure for making geocoded electoral data more findable, accessible, interoperable, and re-usable. Your tasks will be: Setting up the data storage technology and programming the R interface and auxiliary tools for “Electoral Spaces” Testing and assessing the tech stack to ensure it meets researchers' needs for spatial electoral data Supporting data modeling, data ingestion pipelines, and curation workflows Contributing to technical documentation, project outreach, and dissemination Conducting methodological or applied research showcasing the added value of the infrastructure Your profile: Master’s degree in geography, geoinformatics, spatial data science, or a related discipline Technical literacy in geospatial software stacks and strong programming skills in R Strong interest in the application of GIS and spatial data to political and social science research Motivation to complete a PhD thesis c