The Federal Institute for Materials Research and Testing (BAM) stands for safety in technology and chemistry. As a federal scientific and technical authority headquartered in Berlin, we make an important contribution to the protection of people, the environment, and property through research, testing, and consulting. As a federal research institution, we combine science with impact and help ensure that innovations are safely implemented in practice.
Our employees work in an interdisciplinary and international environment at the intersection of science, business, and politics.
Become part of our diverse team!
We offer:
An attractive and modern work environment with excellent infrastructure and state-of-the-art scientific equipment
The freedom to explore your own innovative ideas in research and development
A wide range of professional development and continuing education opportunities, as well as access to high-quality training programs on digitalization topics
Targeted skill development in key technologies for laboratory digitalization through hands-on learning formats
The opportunity to actively shape BAM digitization projects and contribute your own ideas for technical and digital innovations
Flexible working hours and the option to work remotely
A good work-life balance
An appreciative, diversity-oriented work environment with room for your own ideas, digital innovations, and active participation
Opportunities for internal, cross-disciplinary networking, including in our interdisciplinary digitalization communities, as well as participation in team events
Work in national and international networks with universities, research institutions, and industrial companies
Job-ID: J000000280
Location: Berlin
Organization: Section VP.1: eScience
Job Category: Science/Research
Working hours: Full-time / part-time possible
Published: 28.09.2026
Your responsibilities include Your responsibilities include
As a Research Software Engineer (RSE) in the eScience division, you will develop reusable software components and data infrastructures for research data management activities at BAM.
A central focus of the position is the development of a typed scientific schema layer that allows scientific concepts and data models to be defined independently of specific research data platforms and to be reused across different systems. You will work at the interface between scientific software development, data modeling, research data management, and data system integrations. You will contribute to the development of a new software product from an early stage and progressively take on technical responsibility from its architecture, quality, releases, documentation, and integration into BAM’s research data ecosystem.
As a member of the eScience group, you will join an interdisciplinary environment of creative minds. We offer a wide range of challenging tasks at the interface of computer science, data science, and materials research. Our team is renowned for its diversity and vibrant energy. This is your chance to work along international, young, innovative professionals who came together to shape the digitalization of materials research!
You will design, implement, and maintain reusable software components for the structured representation, validation, and processing of scientific data and metadata
You will develop typed scientific data models and schemas, including concepts such as physical quantities and units, controlled vocabularies, relationships, validation constraints, and semantic annotations
You will contribute to the development of a modular Python-based software architecture that separates scientific domain models from platform-specific implementations
You will develop interfaces, adapters, and transformation mechanisms for research data systems such as openBIS, NOMAD, InvenioRDM, and other research data infrastructures and standards
You will design and implement APIs, import/export mechanisms, parsers, AI-integrations, and automated data-processing and ingestion workflows
You will ensure software quality through automated testing, code reviews, documentation, reproducible development workflows, and continuous integration
You will work closely with researchers, other RSEs, data managers, and domain experts to translate scientific requirements into robust technical solutions
You will progressively assume technical responsibility for the software product, including release processes, backlog prioritization, architectural decisions, user request management, and sustainable further development
Your qualifications Your qualifications
Successfully completed scientific university degree (Master’s/Diploma) in Computer Science, Data Science, Scientific Computing, Physics, Mathematics, Bioinformatics, Engineering, or a comparable discipline relevant to the position
Very good programming skills in Python, demonstrated through the development of scientific, data-oriented, or comparable software
Experience working with structured scientific or technical data and developing or applying data-processing, analysis, or integration pipelines
Good knowledge of modern software development practices, such as version control with Git, automated testing, code review, documentation, and reproducible development workflows
Experience with Linux-based development environments and command-line tools
Knowledge of integration of AI/LLM-based tools for data processing and analysis, demonstrated through project work, research, professional experience, or relevant hands-on training
Knowledge of structured data modeling, for example data models or schemas, SQL/noSQL databases, REST APIs, JSON, XML, or comparable technologies
Ability to analyze scientific or domain-specific requirements together with researchers and translate them into technical software concepts
Very good spoken and written English skills; good German skills or willingness to further develop them
Experience with CI/CD, software packaging, and the release of software libraries is desirable
Experience with scientific workflows, high-performance computing (HPC), or cloud environments is desirable
Experience in collaborative and open-source software development projects is an asset
An understanding of the principles of sustainable and reusable research software - particularly maintainability, traceability, interoperability, and reproducibility—is desirable
Knowledge of research data management and the FAIR principles is an asset
Knowledge of scientific data modeling, controlled vocabularies, or the development of data schemas is an asset
Knowledge of research data platforms, repositories, or electronic lab notebooks such as openBIS, NOMAD, InvenioRDM, or comparable systems is an asset
Strong communication and information management skills, a goal-oriented and structured approach to work, the ability to work well in a team and collaborate, flexibility, and the ability to think conceptually, strategically, and innovatively
We show an excerpt and a link, and the full text when the source allows it. Brands and logos shown belong to their owners.
