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Doctoral Researcher in election data (SDC-35)

Organismo
GESIS – Leibniz-Institut für Sozialwissenschaften
País
🇩🇪 Alemania
Lugar
Köln
Puestos
1
Tipo de vínculo
privado

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 election data (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: Identifying election data with sub-national resolution for ingestion into Electoral Spaces Developing and documenting the data ingestion procedure of the Electoral Spaces-infrastructure Testing Electoral Spaces' framework, data model, and technical platform for compatibility with existing election data Supporting the development of data quality tools Conducting methodological or applied research showcasing the added value of the infrastructure Your profile: Master’s degree in political science or a related discipline Strong interest in geocoded electoral data, data collection, harmonization, and management Training in quantitative empirical methods for the social sciences, including good skills in the statistical software R Motivation to complete a PhD thesis closely aligned with the project

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