Your responsibilities include
Contribute to the Euratom CONNECHT-NM SHIELD project "Long-term Structural Health monItoring of nuclear facilities using embedded acoustic Emission and machine Learning for Degradation Detection"
- Develop and evaluate signal processing methods for acoustic emission analysis
- Apply machine learning and statistical methods for event detection, cluster analysis, and classification
- Development and testing of localization methods for acoustic emission analysis of large experimental datasets from laboratory and field tests
- Participation in testing campaigns on concrete structures and high-temperature systems
- Publication of results in international journals and at conferences
Your qualifications
- Successful completion of a master’s or diploma degree in mechanical engineering, materials science, physical engineering, or a comparable field
- Ph.D. in a relevant discipline (e.g., mechanical engineering, materials science, physics, signal processing, electrical engineering) is an advantage
- Excellent knowledge of signal processing and data analysis
- Knowledge of machine learning methods
- Demonstrated experience in acoustic emission analysis or closely related NDT/SHM methods (e.g., ultrasonics, guided waves)
- Experience in one or more of the following areas: Use of fiber-optic measurement systems, simulation of elastic wave propagation, application of machine learning in signal analysis, setup and use of measurement technology
- Solid understanding of elastic wave propagation in solids (e.g., bulk waves, guided waves, dispersion) is required
- Programming experience (e.g., Python, MATLAB)
- Excellent written and spoken English
- Ability to work autonomously and take ownership of tasks—the role requires a high degree of self-organization and initiative
- Knowledge of German is an advantage
- Good communication and information behaviour, goal-oriented and structured way of working, initiative/commitment, ability to work in a team and willingness to cooperate as well as conceptual, strategic and innovative thinking skills
Our Benefits
- Attractive and modern working environment with excellent infrastructure and state-of-the-art scientific equipment (laboratories, BAM Data Store, high-performance computing, etc.).
- Possibility of mobile working up to 60%
- A responsible, interesting, and varied job in a professional and collegial environment.
- 30 vacation days with a 5-day week
- Flexible working hours
- Work in national and international networks with universities, research institutions, and industrial companies
- Attractive location
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.
Your application
We welcome applications via the online application form by 28.07.2026. 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
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