The INM-Leibniz Institute for New Materials is an internationally leading center for interdisciplinary research on materials, and their exploitation in materials-based solutions for a sustainable world with increasing digitalization and medical needs. Our research integrates materials chemistry, biological processes, physical analysis, process engineering and data science. We collaborate with academic and industrial partners all around the world. A focus of our research is Engineered Living Materials (ELMs), an emergent class of materials at the interface between materials science and synthetic biology, with huge potential for sustainable innovation in different technological fields. The multidisciplinary component of our research requires intensive information and data exchange between multiple disciplines. We work on semantically structured data and interfaces, shared workflows, and contribute to engaging the growing ELM community in digitalized research. To coordinate and support the digitalization of the ELM community, we are seeking a Postdoctoral Researcher with expertise in Digitalization and Data Science (f,m,d) to work within the collaborative network MaterialVital Hub, recently funded by the Federal Ministry of Research, Technology and Space (BMFTR) in collaboration with the Galaxy Community Hub. The candidate will be part of a team and work together with experimental scientists and research data management experts at INM-Leibniz Institute for New Materials and with Bioinformaticians at the University of Freiburg. Contribute to the digitalization of synthetic biology data workflows within selected ELM use cases by developing code to create semantic annotated data structures. Development of metadata schemas for typical synthetic biology steps and methodologies in ELM research which are transferable to electronic LabBooks and data platforms of relevance for other researchers within the MaterialVital Hub. Lead the development of ELM-dedicated ontology for interoperability within the MaterialVital Hub in cooperation with researchers and the Galaxy Community Hub and MaterialDigital Platform partners. Demonstrate application cases of Data Science to ELM research based on structured data from the MaterialVital Hub. Support and promote digitalization of the ELM community within the MaterialVital Hub in close interaction with Galaxi Community Hub and MaterialDigital Platform and NFDI. Attend workshops and disseminate your work within the ELM community by presenting at conferences and scientific events. Document your work and report to project coordinators and stakeholders. PhD degree in bioinformatics, systems biology, synthetic biology, biotechnology or related disciplines. Knowledge in automated workflows for (large) data analysis, using Galaxy or similar tools. Experience in the automated analysis of omics and/or imaging data. Interest in working with and for the digitalization of the ELM community. Self-driven and hands-on personality. Organization and prioritization skills. Very good communication skills in English. An emergent hot research topic with multiple opportunities to contribute and interact with the growing community and contribute to its development at an early stage. Direct access to and high visibility in the SynBio and ELM networks at national and international level. An existing team with expertise and drive to move forward digitalization in ELM research. A well-structured on-boarding process and clear responsibilities. A community-oriented, multifaceted work with great scope for creativity. A highly professional and supportive working environment with an open and international culture. Strong support of training and career development towards an outstanding profile as data scientist in synthetic biology research. Flexible working hours and mobile working opportunity. A family-friendly working place. A EG 13 TV-L position (full time). A part time position is also possible. The position is initially for 3 years.