Academic Staff Member (f/m/d) – Computer Science, Mathematics
System Development for Large-Scale 3D Image Reconstruction and Analysis
The new MorphoSphere project develops an advanced data management architecture for distributed, smart, and interactive storage and analysis of series of large 3D tomographic datasets. It integrates large-scale imaging facilities, high-performance computing, data facilities, and scientific communities to optimize data transfer, processing, and visualization, thereby accelerating scientific discovery across diverse research domains.
Exponential growth of imaging data at large-scale imaging facilities, such as synchrotrons, has created major challenges in data handling, analysis, and accessibility. Traditional methods struggle to process petabyte-scale datasets efficiently, limiting researchers’ ability to extract meaningful insights from complex 3D imaging experiments. MorphoSphere addresses this challenge by merging distrib-uted computing, data federation, and artificial intelligence to enable interactive, scalable, and intelligent analysis workflows. This approach reflects a broader shift in scientific research toward data-centric infrastructures that integrate high-performance computing with machine learning, fostering interdisciplinary collaboration and open data practices across different scientific communities.
Organizational unit
Laboratorium für Applikationen der Synchrotronstrahlung (LAS)
Job description
You will develop a modular, flexible, and extensible plugin-based system for large-scale data processing. It will be capable of creating pipelines consisting of both classical image processing algorithms and machine learning–based methods. Within this framework, you will help implement algo-rithms for 3D image reconstruction, including typical pre- and post-processing steps. You will optimize data processing pipelines for diverse hardware and software platforms while ensuring ease of use, reusability, and interactivity. Your work will enable scientists to rapidly design, modify, and execute complex piplelines, making advanced data analysis more accessible and efficient.
Main Tasks
- Develop and assemble a plugin-based framework for large-scale data processing pipelines with cross-technology support (CPU, GPU, multi-node systems)
- Integrate and implement image processing algorithms, particularly for 3D imaging.
- Optimize system performance for computing infrastructures at partner institutions.
- Implement high-level data processing pipelines creation in Python, a visual programming tool and integrate them into an online interactive platform
Starting date
01.03.2026
Personal qualification
You have a Master’s degree in computer science, mathematics, or related disciplines. Required Skills: Good proficiency in programming, particularly with C and Python; work experience with image-processing; fluency with Linux; experience with machine learning, networking technolo-gies, HPC and parallel programming with OpenCL/CUDA is a plus.
This is what we offer
Become a member of staff of the only German University of Excellence that conducts large-scale research on the national level. Work under excellent working conditions in an international environment and be active in research and academic education for our future. Benefit from specific training when starting your job and from a wide range of further qualification offers. Use our flexible working time models (flexitime, work from home), our sports and leisure offers, as well as our child and holiday care services. We also pay a share of EUR 25/month in the Job Ticket Baden-Württemberg. Enjoy a large variety of dishes, snacks, and beverages at our canteens.
Salary
Salary category 13 TV-L, depending on the fulfillment of professional and personal requirements.
Contract duration
3 years
Application up to
03.01.2026
Contact person in line-management
For further information, please contact Prof. Dr. Tilo Baumbach, Email: tilo.baumbach@kit.edu.
Please apply online using the button below for this vacancy number 519/2025.
Vacancy number: 519/2025
We prefer to balance the number of employees (f/m/d). Therefore we kindly ask female applicants to apply for this job. Recognized severely disabled persons will be preferred if they are equally qualified.Contact
Personnel Support is provided by:
Personalservice (PSE) - Human Resources
Ms Kaiser
Phone: +49 721 608-22438,
Laboratory for Applications of Synchrotron Radiation (LAS)