Research assistant (m/f/d) with a PhD in Chemistry, Physics, Materials Science or a related field
Salary group A 13 BBesO / remuneration group 13 TVöD
Official/permanent employment relationship
Suitable for full-time or part-time work
The Bundesanstalt für Materialforschung und -prüfung (BAM) is a materials research organization in Germany. Our mission is to ensure safety in technology and chemistry. We perform research and testing in materials science, materials engineering and chemistry to improve the safety of products and processes. At BAM we do research that matters. Our work covers a broad array of topics in the focus areas of energy, infrastructure, environment, materials, and chemistry and process engineering.
The position can be filled by either a salaried employee or a civil servant. If you are subsequently appointed as a civil servant, you must meet the requirements for civil service and career law. Appointment as a civil servant is initially possible in salary grade A XXX BBesO.
We offer:
- Access to high-quality continuing education and training on digitalization topics such as programming, research data management, AI applications, and machine computing in science.
- Networking and exchange in our interdisciplinary digitalization communities and at BAM digitalization events to develop innovative solutions together with our experts.
- Targeted acquisition of skills in key technologies for laboratory digitalization—modern programming paradigms, connection to the electronic laboratory notebook, and development of metadata formats and ontologies—through practical learning formats such as workshops, online courses, and collaborative training with bundled knowledge sources.
- Opportunity to actively participate in shaping BAM digitization projects and to contribute your own ideas for digital innovations.
We are looking for talented people to join us.
- Job-ID: J000000118
- Location: Berlin
- Start date: zum nächstmöglichen Termin
- Organization: Division 6.7: Materials Synthesis and Design
- Job Category: Science/Research
- Working hours: Full-time / part-time possible
Your responsibilities include:Your responsibilities include:
- Establishing, expanding and contributing to the standardisation of meta- and research data management using ELN/LIMS systems and ontologies/knowledge graphs
- Further development, standardisation and maintenance of the code for hardware control, orchestration and data management of the Self-Driving Labs/Materials Acceleration Platforms (SDLs/MAPs) developed within the department
- Integration of new hardware and software tools into the SDL/MAP technology stack
- Application and implementation of machine learning and artificial intelligence methods in the context of active learning for feedback loops in MAPs/SDLs
- Development of ideas and research concepts, preparation of grant applications and acquisition of third-party funding
- Coordination and management of research and development projects on data management and SDLs/MAPs (e.g. with a focus on workflows, ELN/LIMS integration, backend and frontend in SDLs/MAPs)
- Supervision and academic guidance of early-career researchers
- Preparation of reports, posters, project reports, etc.
- Publication of results in international peer-reviewed journals and presentation at national and international level
- Collaboration with internal and external experts on the topics of Self-Driving Labs, Materials Acceleration Platforms, ontologies, knowledge graphs, data management, and ELN/LIMS
- Active involvement in the field of materials, specifically in the areas of advanced materials and material design
- Active involvement in the MAPs@BAM initiative to support laboratory automation
Your qualifications:Your qualifications:
- Successful scientific universitiy degree specialising in chemistry, physics, computer science, materials science or a comparable field and a very good PhD
- Extensive knowledge and practical experience in working with and creating knowledge graphs and ontologies (e.g. the MaterialDigital project) (demonstrated by publications or software contributions)
- Experience in the field of implementation and hardware integration for laboratory automation or high-throughput methods (demonstrated by successfully completed modules or publications)
- Very good programming skills (particularly in Python) (demonstrated by published software contributions or publications)
- Knowledge and practical experience with research data management and ELN/LIMS systems (demonstrated by successfully completed modules, publications, or software contributions)
- Experience in the field of machine learning and artificial intelligence (e.g. Bayesian optimisation, neural networks), as well as with code management tools (e.g. GitHub), is required, also demonstrated by publications or software contributions
- Experience in securing third-party funded projects
- Extensive publication experience (more than four publications as first or last author)
- Experience in supervision of young scientists
- Confirmed practice in publication and presentation of scientific results
- Very good written and spoken English
- Knowledge of German is an advantage
- Good communication and information management skills, a goal-oriented and structured approach to work, initiative/willingness and ability to take on tasks, ability to work in a team and cooperate, as well as a willingness to learn
Our BenefitsOur Benefits
- 30 vacation days with a 5-day week
- Work in national and international networks with universities, research institutions, and industrial companies
- Attractive and modern working environment with excellent infrastructure and state-of-the-art scientific equipment (laboratories, BAM Data Store, high-performance computing, etc.).
- Company pension scheme (VBL)
- Possibility of mobile working up to 60%
- Subsidy for the Job Ticket
30 vacation days with a 5-day week; Work in national and international networks with universities, research institutions, and industrial companies; Attractive and modern working environment with excellent infrastructure and state-of-the-art scientific equipment (laboratories, BAM Data Store, high-performance computing, etc.).; Company pension scheme (VBL); Possibility of mobile working up to 60%; Subsidy for the Job Ticket
Your application:Your application:
We welcome applications via the online application form by 31.07.2026. Alternatively, you can also send your application by post, quoting the Job-ID to:
Bundesanstalt für Materialforschung und -prüfung
Referat Z.3 - Personal
Unter den Eichen 87
12205 Berlin
GERMANY
www.bam.de
BAM promotes professional equality between women and men. We therefore particularly welcome applications from women. At the same time, we strive to reflect social diversity. Every application is therefore welcome, regardless of gender, cultural or social background, religion, ideology or sexual identity.
In addition, BAM has set itself the goal of promoting the professional participation of people with severe disabilities. The fulfillment of the job requirements is considered on an individual basis. Severely disabled persons or persons of equal status will be given preferential consideration if they are equally qualified.
The advertised position requires a low level of physical aptitude.
ContactContact
Fachbereichsleiter 6.7
Richard-Willstätter-Straße
12205 Berlin
0308104-5571
bastian.ruehle@bam.de
Abteilungsleiterin 6.
Richard-Willstätter-Straße
12205 Berlin
0308104-1133
franziska.emmerling@bam.de