The project & your career perspective:
This position is funded by the Cluster of Excellence EXC 2075 and is part of the Project Network „Bayesian Inference for Stochastic Models: Generalized Methods for Forward and Backward Uncertainty Quantification (Bayes 2.0)“.
Imaging modalities, such as computerized tomography (CT), are concerned with recovering information about the interior structure of a studied object in a non-invasive way. In many medical or industrial applications, the quantity of interest changes during the data acquisition. Thus, the actual image reconstruction step requires suitable a priori information on the dynamics. This can be incorporated explicitly, e.g. via diffeomorphic motion models, or implicitly by interpreting motion as an inexactness in the forward model. Conventional approaches treat such model deviations deterministically, ignoring their stochastic nature and hindering uncertainty quantification.
This project develops a Bayesian framework for inverse problems with inexact forward operators. Model inexactness will be interpreted first as a random variable and then as a stochastic process to capture time-dependent deviations. The main goal of the project is to explore suitable priors for both the unknown and the model error, and to develop computationally feasible approaches for posterior exploration.
You will be a member of Prof. Bernadette Hahn-Rigaud‘s working group “Optimization and inverse Problems” at the Institute of Mathematical Methods in Engineering, Numerical Analysis and Geometric Modeling (IMNG).
Your tasks:
Stochastic modeling of model inexactness
Derivation of priors for unknown parameters and model error, e.g. based on physical constraints
Development of efficient posterior exploration methods and dimension reduction techniques, e.g. via likelihood-informed subspaces
Close collaboration with our network partners
Publication of research results
Active participation in SimTech events (Status seminars, Project Network meetings, further events)
Your qualifications (don’t hesitate to apply – enthusiasm can compensate some gaps):
Very good Master’s degree or PhD in mathematics, natural sciences, engineering or a related field, ideally having written the master’s or doctoral thesis in the area of applied mathematics
You have thorough knowledge in one or more of the following mathematical subjects:
Inverse problems
Bayesian statistics
Stochastic processes
Uncertainty quantification
Experience with programming languages and frameworks for Bayesian modeling and uncertainty quantification, e.g. Python or C++/Julia
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
We offer (looking for anything else? Ask us!):
An inspirational and supportive research environment at the Cluster of Excellence SimTech with ample networking opportunities
A nationally and internationally well-connected research group
Fully funded conference visits and a fully funded research stay abroad
Diverse and responsible tasks in a growing interdisciplinary and intercultural team
You will be part of the SimTech Graduate School
Training programs to support your first steps as an early career scientist
The University and the Cluster of Excellence:
The University of Stuttgart represents outstanding, world-renowned research and first-class teaching in one of Europe's most dynamic industrial regions. As a reliable employer, the university supports and promotes the academic careers of its researchers. It is proud of its employees, who currently come from over 100 different countries. The university is a partner for knowledge and technology transfer and focuses on multidisciplinarity.
The Stuttgart Center for Simulation Science (SC SimTech) constitute a long-standing prime example of establishing and structurally supporting interdisciplinary research. SC SimTech serves as the institutional backbone of the EXC 2075. The SC SimTech, including the EXC 2075, is an interdisciplinary research center with more than 200 scientists of different ages, gender identities, nationalities and different subject areas, jointly performing research towards a common goal: We target a new class of modeling and computational methods based on available data from various sources, in order to take the usability, precision and reliability of simulations to a new level.
Diversity and work-life balance:
At the University of Stuttgart, we actively promote diversity among our employees. We have set ourselves the goal of recruiting more women scientists and employing more people with an international background, as well as people with disabilities. We are therefore particularly pleased to receive applications from such people. Regardless, we welcome any good application. Women who apply will be given preferential consideration in areas in which they are underrepresented, provided they have the same aptitude, qualifications and professional performance. Severely disabled applicants with equal qualifications will be given priority.
As a certified family-friendly university, we support the compatibility of work and family, and of professional and private life in general, through various flexible modules. We have an employee health management system that has won several awards and offers our employees a wide range of continuing education programs. We are consistently improving our accessibility. Our Welcome Center helps international scientists get started in Stuttgart.
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, one letter of reference, as well as academic certificates, until December 8th, 2025. The starting date is negotiable. If you have any questions regarding this application, please contact us via Bernadette.Hahn@imng.uni-stuttgart.de.
Information in accordance with Article 13 DS-GVO on the processing of applicant data can be found at https://careers.uni-stuttgart.de/content/privacy-policy/?locale=en_US.
Stellenmerkmale
Dein Beschäftigungsumfang
Vollzeit (befristet)
Dein Gehalt
E13
Dein Arbeitsplatz:
vor Ort
Dein Büro:
Raum Stuttgart
Ansprechpartner:in
Bei Fragen
Frau Prof. Dr. Bernadette Hahn-Rigaud