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About the Role

Within the DFG project "Berlin – Views of a Metropolis. An annotated image corpus of public space in Berlin," a corpus of diverse representations of Berlin's public space, varying in time, style, and content, is to be compiled and enriched for reuse in AI models. The images will be annotated regarding their temporal and geographical location, representational style, and content. Based on this, machine learning methods will be developed and tested to automatically recognize and classify Berlin representations temporally and spatially.

Responsibilities

• Identification, research, and documentation of objects in Berlin's urban space using relevant databases and sources.
• Performing manual and AI-supported image annotations according to specified guidelines and using domain-specific vocabularies and master data.
• Technical and formal quality control of digitized items, metadata, and annotations.
• Development and documentation of annotation guidelines for the data corpus objects.
• Importing data from various source systems into project-internal work environments.
• Preparing datasets for training AI models and contributing to research data management.
• Coordinating with cooperation partners on data deliveries, metadata, and terms of use.
• Preparing materials for project meetings, workshops, presentations, and publications, and contributing to project documentation.

Requirements

• Successfully completed relevant university degree (Bachelor's or FH Diploma) in Library and Information Science, Archival Science, Documentation, Museology, Digital Humanities, or Data Management.
• Experience in digital object indexing and in the structured capture, maintenance, and quality assurance of data and metadata from the cultural heritage sector.
• Experience with museum and/or archival collection databases.
• Experience with common metadata standards, controlled vocabularies, and master data from the cultural heritage sector.
• Very good German language skills (written and spoken) and English skills sufficient for confident use of English software interfaces and technical documentation.
• Strong team and communication skills.
• Willingness and ability to learn new applications, especially tools for data management, data structuring, and image annotation.

Skills

• Wikidata
• Linked Open Data systems
• Research data management
• FAIR principles
• Basic programming skills
• Urban history
• Cultural heritage of Berlin

Location

• Berlin

Work Type

• Part-time
• Fixed-term

Experience Level

• Entry-level
• Mid-level

Education Level

• Bachelor's degree
• FH Diploma

Salary/Compensations

• Entgeltgruppe 11 TV-L

Benefits

• Active onboarding process
• Family-friendly work environment
• Flexible working and meeting times
• Varied, future-oriented, and responsible area of responsibility
• Professional development opportunities
• Support for professional development
• Supplementary pension (VBL)
• 30 days annual leave
• Flexible working hours (flexitime)
• Annual special payment
• Capital city allowance up to €150 monthly
• Alternatively, BVG-Jobticket + difference amount
• Subsidized use of canteens and sports programs of FU Berlin

About the Company

• The Zuse Institute Berlin is an interdisciplinary research institute of the state of Berlin that combines Artificial Intelligence and Scientific Computing with application-oriented mathematics and High-Performance Computing.
• Together with partners from science, technology, and industry, we develop computer-aided methods to solve socially relevant problems and provide state-of-the-art high-performance computing, AI, and data management infrastructures.

Equal Opportunity

• The Zuse Institute Berlin is committed to diversity, equal opportunities, and respectful interaction.
• To increase the proportion of women in areas where they are underrepresented, applications from women are expressly welcome.
• Regardless of this, we welcome applications from all qualified individuals regardless of age, disability, ethnic or social origin, religion or belief, or sexual orientation or gender identity.