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Semantic Data Architect Location: Remote, Hannover (Germany) Employer: German National Library of Science and Technology (TIB) Contract: Full-time (39.8 hours/week), initially limited to two years with envisioned extension. Limited suitability for part-time. Salary: Pay scale group 13 TV-L (German public service collective agreement) Your Challenge Work in an interdisciplinary team on the development and operation of semantic research data infrastructures for chemistry, materials science, and engineering. Act as a bridge between scientific disciplines, ontology development, and software development. Develop cross-disciplinary semantic models, applications, and services, and test AI-supported approaches for efficient ontology development and curation. Semantic Modelling: Collaboration with partners in chemistry, engineering, computer science, and libraries Evaluation and implementation of LLM-based tools for AI-assisted ontology development and curation (human-in-the-loop) Development and maintenance of domain-specific ontologies and controlled vocabularies for materials science, manufacturing engineering, process engineering, and chemistry Application, mapping, and alignment of standards: Metadata4Ing, MSEO, BFO, DataCite, DCAT-AP Design of metadata schemas and generic protocol structures for experiments and processing workflows Development and maintenance of knowledge graphs (RDF, SPARQL) Conceptual System Development: Coordinating the conceptual (further) development of the RDM system architecture from a "big-picture" perspective Collaborative requirements engineering: translating domain requirements into technical specifications for semantic annotation applications Quality assurance of system implementations regarding semantic correctness, FAIR compliance, and interoperability Helping to design knowledge graph interfaces and SPARQL query interfaces Your Profile Must-Have: Completed academic degree (Master's, university diploma, or equivalent) in computer science, chemistry, materials science, engineering, information science, computational linguistics, linguistics, digital humanities, data science, or related field with a demonstrable connection to knowledge modelling, semantic technologies, or information structuring Familiarity with FAIR data principles and modern research data management standards Knowledge of metadata schemas (DataCite, Schema.org, DCAT) Experience in modelling metadata schemas and/or controlled vocabularies Excellent understanding of software development processes and ability to bridge domain experts and developers Knowledge of version control (Git) and CI/CD workflows High degree of self-organization and ability to work independently Excellent written and spoken English skills Desirable Additions: Experience with ontologies in chemistry, materials science, or engineering Experience with ontology development tools (ROBOT, ODK, Protégé) Knowledge of LinkML and SSSOM Experience with AI-supported ontology development (LLMs like OntoGPT, CurateGPT, LLM-supported ROBOT workflows) Experience with data repositories, electronic lab notebooks, Semantic MediaWiki, or terminology services Knowledge of German is a plus, but not required What We Offer Job in public service oriented towards common good (TV-L, pay group 13) Special annual payment, 30 days vacation per year (5-day week), plus additional days off on Dec 24 and Dec 31 Flexible working hours (flexitime), mobile/remote work options, work-life balance support Modern workplace in central Hannover with collegial, attractive environment Internal/external further education, workplace health promotion, supplementary pension scheme (VBL) Employee discounts in canteens and access to university sports Independent, future-oriented activities with room for personal development Portfolio of technology components (ORKG, OpenResearch.org, TIB AV-Portal, DBpedia.org) Funding for technical equipment, conference and research visits This position is part of TIB's Research and Development Department, collaborating with L3S Research Center at Leibniz University Hannover within the Leibniz Joint Lab Data Science & Open Knowledge.