PHD RESEARCHER POSITION "Dynamic image reconstruction in Phase-Contrast Tomography"
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Monthly Salary:
Posted on:
3 days ago
Vacancies:
1 Vacancy
Job Summary
| Position-ID: | 1800 |
| Faculty/ Facility: | Mathematics and Physics |
| Institute/ Facility: | Mathematics and Physics : IMNG - Institute of Mathematical Methods in Engineering Numerical Analysis and Geometric Modeling |
| Research Association: | N/A |
| Teaching Obligation: | No |
| Application deadline: | 01/20/2026 |
| Anticipated Start Date: | 02/01/2026 |
The project & your career perspective:
This position is funded by the BMFTR (Federal Ministry of Research Technology and Space) and is part of the collaborative research project Phasen- und absorptionsinformierte Bildgebung von Gewebe: Intelligente Rekonstruktionsverfahren für die medizinische Diagnostik (PhabiMed).
X-ray tomography enables the visualization of internal structures of the human body without invasive intervention and is widely used for the diagnosis of various diseases for example of the lung. Conventional computed tomography (CT) relies on X-ray absorption and therefore provides only limited soft-tissue contrast. Phase-contrast CT (PCT) additionally exploits diffraction effects of X-rays enabling the visualization of weakly absorbing structures.
In addition to the tomographic reconstruction PCT requires a phase-retrieval step which so far relies on idealized assumptions. These assumptions are generally not met when using clinically relevant X-ray sources. The aim of this collaborative project between the Universities of Stuttgart and Göttingen in cooperation with application partners is therefore the development of efficient and high-resolution reconstruction methods for clinical applications.
A particular focus is placed on handling object motion as PCT measurements are significantly more sensitive to motion effects than conventional CT. The subproject at the University of Stuttgart focuses on the development of dynamic reconstruction methods that enable temporally highly resolved and artifact-free visualization of tissue changes. To this end data-driven approaches will be combined with model-based methods to ensure both efficient reconstruction and high reliability of the results.
You will be a member of Prof. Bernadette Hahn-Rigauds working group Optimization and inverse Problems at the Institute of Mathematical Methods in Engineering Numerical Analysis and Geometric Modeling (IMNG).
You will collaborate closely with the research partners at the University of Göttingen and the industry/application partners of the project.
- Modeling of dynamic PCT considering tissue deformations
- Development of learned iterative methods to compensate for unknown object motion
- Integration of physical motion models and neural networks for accurate estimation of model deviations
- Coupling of absorption and phase information
- Optimization of methods for large datasets
- Close collaboration with our project partners
- Publication of research results
- Active participation in project events (Status meetings Project workshops research visits at the partner institutions further events)
- Very good Masters degree or PhD in mathematics natural sciences engineering or a related field ideally having written the masters thesis in the area of inverse problems
- You have thorough knowledge in one or more of the following mathematical subjects:
- Inverse problems
- Computational imaging
- Machine learning
- Numerical analysis
- Physical modeling
- Experience in implementing numerical and computational methods using programming languages such as Python or C
- You are motivated to work in an interdisciplinary project team
- Proficiency in English is required knowledge in German is welcome but not compulsory
- We search for an open-minded person with good communication skills
- An inspirational and supportive research environment
- A nationally and internationally well-connected research group
- Funded conference visits and research stays at the partner institutions
- Diverse and responsible tasks in a growing interdisciplinary and intercultural team
Application procedure:
Please apply via the career portal of the University of Stuttgart and submit your complete application including one-page motivation letter academic CV three names of people who would be willing to write a letter of reference as well as academic certificates until January 19th 2026. The starting date is negotiable. If you have any questions regarding this application please contact us via .
Type of Funding:Position as Employee at the University of Stuttgart
Compensation:EG TV-L 13
Location:Stuttgart Campus Vaihingen
If Location other than Stuttgart or additional location(s): N/A
Mail:
Phone:49 5
Website: targetblank> Not translated in selected language
Required Experience:
IC
Key Skills
- Intelligence Community Experience
- Python
- Spss
- Microsoft Word
- R
- Regression Analysis
- Windows
- Stata
- Microsoft Powerpoint
- Research Experience
- Data Modeling
- Writing Skills
