Jobs@LAS

• Academic Staff Member (f/m/d) – Computer Science, Mathematics System Development for Large-Scale 3D Image Reconstruction and Analysis

Academic Staff Member (f/m/d) – Computer Science, Mathematics
System Development for Large-Scale 3D Image Reconstruction and Analysis

Category

Job description

You will develop a modular, flexible, and extensible system for large-scale 3D image processing (around 30 GB input data per data set, thousands of data sets per week). The system will create image processing pipelines in a graph-like manner and ensure that all available ressources (GPUs in a multi-GPU server and also multiple such servers) are used to efficiently execute it. It will be possible to use both classical image processing algorithms and machine learning-based methods as nodes in such a graph and to use the system from multiple programming languages (C, Python). You will also help implement the nodes, especially algorithms for 3D image reconstruction, including typical pre- and post-processing steps. You will optimize the system for different hardware platforms. Your work will enable scientists to rapidly design, modify, and execute complex image processing pipelines, making advanced image analysis more accessible and efficient. 

Main Tasks

• Develop and assemble a plugin-based system for large-scale image processing pipelines with cross-technology support (CPU, GPU, multi-node systems) and with focus on zero-copy data paths, efficient utilization of high-speed interconnects, and optimal scalability across multiple GPUs and GPU nodes
• 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

Personal qualification

PhD in computer science, mathematics, or related disciplines; alternatively masters in one of the named disciplines with 2+ years work experience. Required Skills: work experience with design/implementation of cross-technology systems (CPU, GPU, clusters) and parallel programming with CUDA/OpenCL; good proficiency in programming, particularly with C and Python, fluency with Linux; experience with image processing, machine learning, networking technologies is a plus.