Research Infrastructure Specialist (Postdoc) for Trusted Research Environments (DSS-26)

The department Data Services for the Social Sciences offers sustainable infrastructures and services for data management, curation, and long-term preservation. Its mission is to foster FAIR data, open science, and reproducible research in the quantitative and computational social sciences. This includes archiving services with different curation levels for individual researchers, projects, and institutions, providing access to archived data, including access to sensitive data, the data registration agency da|ra, and data management trainings.

We also operate the GESIS Secure Data Center, our Trusted Research Environment (TRE) for providing controlled access to sensitive research data in the social sciences. Building on this infrastructure, the project RIDLOP (Research Infrastructure for Data from Large Online Platforms) develops the next generation of the Secure Data Center toward a scalable, compliant, and remotely accessible research environment for different types of sensitive social science data collected from online platforms and other types of digital behavioral data. 

• Translation of TRE governance, research, and data-access requirements into technical specifications for external IT developers
• Coordination between researchers, IT specialists, data curators, legal/data protection experts, governance bodies, external technology providers, and user communities
• Design, testing, and documentation of secure TRE workflows for data ingestion, access management, analysis, output review, archiving, and reproducible research
• Development and adaptation of lightweight tools, scripts, templates, and prototypes for TRE operations, user support, and reproducible research workflows
• Support for the operational implementation of legal requirements (e.g. GDPR, Digital Services Act, AI Act, copyright), research-ethics, and Five Safes requirements in technical and organizational TRE processes

• A completed master’s degree and a ompleted (or soon-to-be-completed) doctoral degree in a related field such as for example computational social science, social sciences, information systems, data science, computer science, including peer-reviewed publications in relevant academic outlets
• Strong practical experience with R, Python, reproducible research workflows, and data-intensive empirical research
• Good understanding of secure research environments (for example, access-control models, remote desktop solutions, audit logging, APIs, databases, or workflow automation) and willingness to engage with adjacent areas of IT architecture
• Experience with sensitive data (for example social science data, digital behavioral data, social media data, platform data, linked data, or comparable restricted research data)
• Strong ability to communicate complex technical, legal, and methodological requirements to both specialist and non-specialist audiences in very good written and verbal English (German language skills are not expected at first but will be required by the start of the tenure process)

• A fast growing, international and interdisciplinary working environment with strong ties to regional and international labs and experts in related fields 
• Interdisciplinary team and diverse opportunities for networking and further qualification  
• Flexible working hours and regulations for mobile working 
• 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 
• Generous support for your pension provision as a direct insurance policy
• Promotion of your skills through further training measures