Research position: Visualizing 3D failure mechanisms with X-Ray imaging and Artificial Intelligence

We are offering a research position within the field of in-situ testing with X-Ray computed tomography. Research position: Visualizing 3D failure mechanisms with X-Ray imaging and Artificial Intelligence

• Application deadline: 31. March 2026
• Publication date: 1. March 2026
• Start-date: At the earliest possible date.
• Scope of work: Full-time position
• Id no.: 00004865

Description

The aim of the research is to investigate how damage and failure mechanisms in heterogeneous materials such as additively manufactured metal structures and fibre-reinforced materials can be visualized using computed tomography. Specifically, we are interested in answering the question which quality of results can be attained with modern 3D image processing algorithms such as Digital Volume Correlation (DVC) in combination with in-situ X-Ray tests. With DVC algorithms serving as the baseline to measure strain fields, this project will also investigate how well AI methods such as Convolutional Neural Networks can compute strain maps between different deformation states, possibly with much lower computational effort as compared to the current state of the art. You will be part of a team of researchers and engineers that jointly works within the larger scope of experimental mechanics and numerical simulation. This position can be further tailored to accommodate either a doctoral student or a postdoctoral researcher. In the case of a doctoral student, supervision and guidance will be provided. In the postdoctoral case, you will be expected to design your research independently. Practical experience with computed tomography is not required, as images will be generated by dedicated specialists.

Your background should necessarily include in-depth understanding and prior experience in these areas:

 

• Continuum mechanics and constitutive laws for material behaviour
• Good Python skills to facilitate all of the programming tasks
• Experience with Finite Element simulations to create digital twins of the experiments
• A good understanding of mathematics and physics on the level of an engineering degree
• Desirable: experience with image processing or volumetric data analysis
• Desirable: experience with machine learning algorithms

 

We offer

 

• A research environment across the University of Freiburg and the Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, allowing you to interact with a multitude of different research groups and different perspectives
• Access to excellent research infrastructure including material testing facilities, imaging and microscopy devices, and state-of-the-art workshops for building custom electronic and mechanical research instrumentation
• Unlimited access to a number of computed tomography setups with in-situ testing capability
• High-performance computer resources

The position will be initially offered for three years. The salary will be determined in accordance with E13 TV-L.

Application

Please send your application in English including supporting documents citing the reference number 00004865, by 31. March 2026 at the latest. Please send your application to the following address in written or electronic form:

Universität Freiburg
Professur für Nachhaltige Ingenieursysteme
Georges-Köhler-Allee 401a

For further information, please contact Herr Dr. Georg Ganzenmüller on the phone number +49 761 203-96784 or E-Mail georg.ganzenmueller@inatech.uni-freiburg.de.