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.