Job description

The scientific activity takes place within the DFG-funded research group FOR 3022 “Ultrasonic monitoring of fiber-metal laminates with integrated sensors” in subproject 4 “Automated data-driven damage detection”. With the help of guided ultrasonic waves in fibre-metal laminates, damage within the material is to be detected and, if necessary, even characterized. Both mathematical models (differential equations) and (synthetic and experimental) measurement data are used for this purpose. Machine learning methods (in particular Physics Informed Neural Networks) will be used, adapted, analyzed and further developed for this purpose.

What tasks await you in the project and in our team?

• You will conduct research in the field of physics-informed neural networks (PINNs, AG Lorenz) for damage detection in fiber-metal laminates and investigate and develop the methods both theoretically and numerically.
• You regularly present the results at interdisciplinary internal project meetings and at national and international conferences.
• You will publish research results and write reports.

What can we offer you?

• Integration into the highly motivated, interdisciplinary, multicultural and agile ZeTeM team
• Family-friendly working environment
• Company fitness and job ticket
• Further training opportunities (professional and social)
• Networking with industry and research (national and international)
• Applied research with practical and industry-related topics

Requirements

• You have a university degree (Master's degree or university diploma) in mathematics, computer science, industrial mathematics, engineering (with a strong focus on mathematics), or a comparable degree.
• You enjoy innovation and development and are willing to continue your education in this area.
• You have experience with programming in Python.
•  You enjoy familiarizing yourself with new and complex contexts, like to organize and work in a team.
• You have a very good command of written and spoken English and a basic knowledge of German.

What would be an additional advantage?

• Experience in university teaching and its integration into the specific curriculum
• Previous experience in the development of innovative projects
• Previous experience in the cooperation of research institutions with (regional) companies
• Since the team is characterized by agile working methods, the ability to work in a team is a very important selection criterion in addition to professional aptitude.

General Information

Open to unconventional approaches in research and teaching, the University of Bremen has retained its character as a place of short distances for people and ideas since it was founded 50 years ago. With a broad range of subjects, we combine exceptional performance with great potential for innovation. As an ambitious research university, we stand for the approach of research-based learning and a strong focus on interdisciplinarity. We actively shape scientific cooperation worldwide in a spirit of partnership.

Today, around 23,000 people learn, teach, research and work on our international campus. In research and teaching, administration and operations, we are firmly committed to the goals of sustainability, climate justice and climate neutrality. Our Bremen spirit is expressed in the courage to try new things, in supportive cooperation, in respect and appreciation for one another. With our study and research profile and as part of the European YUFE network, we assume social responsibility in the region, in Europe and the world.

The university is family-friendly, diverse and sees itself as an international university. We therefore welcome all applicants regardless of gender, nationality, ethnic and social origin, religion/belief, disability, age, sexual orientation and identity.

As the University of Bremen intends to increase the proportion of female employees in academia, women are particularly encouraged to apply.

Severely disabled persons with essentially equal professional and personal qualifications will be given priority.

If you have any questions, please contact: Prof. Dr. Dirk Lorenz, d.lorenzprotect me ?!uni-bremenprotect me ?!.de.

Please send your application documents (CV, diploma or master's certificate and project experience) with the reference number A339-24 by 03.01.2025 as a PDF file by unencrypted electronic mail to Prof. Dr. Dirk Lorenz, d.lorenzprotect me ?!uni-bremenprotect me ?!.de

or by post to

University of Bremen
Faculty 3
Prof. Dr. Dirk Lorenz
Bibliothekstr. 5
28359 Bremen

Please send us only copies of your application documents (no folders), as we cannot return them. They will be destroyed at the end of the selection process.

Any costs for the application procedure cannot be reimbursed.