Computer scientist for knowledge contextualisation (m/f/d)
Museum für Naturkunde - Leibniz Institute for Research on Evolution and Biodiversity (MfN), Berlin
Our Mission: Discovering and describing life and earth - with people, through dialogue.
The Museum für Naturkunde Berlin (MfN) is an excellent and integrated research museum of the Leibniz Association with an international reputation and globally connected research infrastructure. MfN is active in three closely interlinked fields: collection-based research, collection development, and research-based public and educational outreach. Over the next ten years, the Museum für Naturkunde Berlin will build up a science campus for nature and society in the centre of Berlin as science hub, together with the Humboldt Universität zu Berlin. New laboratories and workplaces for cutting-edge research will be established. One of the world's most comprehensive natural history collections with over 30 million objects will be housed in state of the art buildings as well as fully digitized. The implementation of the so-called Zukunftsplan (future plan), funded with a total of 660 million euros from the Federal Government and the State of Berlin, strongly relies on interdisciplinary national and international partners.
Become part of our team.
Position: Computer scientist for knowledge contextualisation (m/f/d)
Work schedule: Full time; equivalent to 39 hours and 24 minutes per week
Duration: as soon as possible; limited for 48 months
Salary level: E 13 TV-L
Code: 75/ 2022
Within the framework of the Future Plan, we are developing the collection of the Museum für Naturkunde Berlin in a sustainable way, i.e. conservationally secured, digitally recorded and made accessible for innovative uses. In doing so, we are developing the collection into an open, digital-analogue research infrastructure that can meet future scientific, social and technological requirements. As a modern research and information infrastructure, our collection will be fully integrated into the European landscape, designed to be analogue and digitally interoperable, thus enabling holistic access. Of central importance is the embedding of the collection in the global and historical context as well as the presentation of this complex structure.
- analysis, conception and development of methods and tools for the communication and presentation of complex scientific contexts.
- analysis and conception of mechanisms for data networking as well as further innovative methods in the field of semantic web (in particular object data, taxanomic data, georeferencing, personal data, historical contexts, external data sources)
- university degree in data science, computer science, geoinformatics or bioinformatics or in an engineering or natural science degree programme that includes aspects of these disciplines, doctorate advantageous or appropriate professional experience for this position in the aforementioned areas and participation in corresponding reference projects.
- very good knowledge and practical experience in the conception and architecture of databases
- proof of active scientific publication activity
- very good knowledge and practical experience in the field of Linked Open Data analysis, semantic technologies or ontology development
- very good knowledge and experience in processing XML files (e.g. with XPath, XSLT, XQuery), as well as in semantic technologies and standards (OWL, RDF, SKOS, SPARQL, triple store, XML and graph databases)
- experience in the development of vocabularies / ontologies in RDF / OW
- very good knowledge and practical experience in the conception, design and implementation of web-based applications
- very good knowledge in visualisation of data and creation of visualisation concepts and in dealing with frameworks for visualisation (e.g. D3.js)
- knowledge and experience in programming with modern web frameworks (e.g. React, Angular, Vue.js) and in UX design are advantageous
- very good knowledge and practical experience in several of the following areas: Implementation of data science pipelines, identifier systems, data publishing and archiving
- very good knowledge and practical experience in the strategic conception and development of data flows, standards and the architecture of specialised databases
- knowledge of Linux shell and Linux tools (e.g. gep, dsed) and of programming shell scripts
- experience in implementing scalable services with Docker or Kubernetes
- experience in leadership positions, e.g. team leadership as well as in teamwork, ideally also in changing teams and in time-bound projects. Experience in project management is advantageous.
- interest in transformations from various data formats (e.g. relational, XML or unstructured text) into semantic representations
- independent and structured work
- good communication and presentation skills
- very good knowledge of German and English, both written and spoken
In support of equal rights applications from qualified women are particularly welcome. Handicapped individuals will be given preference in cases of identical qualifications.
We look forward to receiving your application with the usual documents (cover letter, curriculum vitae, certificates) by 26.08.2022, preferably via our online application portal at
For information on the application procedure, please contact email@example.com.
By sending your application, you provide us with your information for the purpose of processing your application by the Museum für Naturkunde. Your data will be kept strictly confidential at all times. Once we have received your application documents, they will be entered into our database. Your data will be stored on our server. In doing so, we observe the provisions of the data protection laws.
The Museum für Naturkunde has set itself the goal of promoting a work-life balance and has been awarded the certificate berufundfamilie audit of berufundfamilie gGmbH - an initiative of the Hertie Foundation.
Further information can be found under: https://www.museumfuernaturkunde.berlin/en/uber-uns/jobs-und-karriere/arbeiten-am-museum-fur-naturkunde/reconciling-work-and-family-life-audit