Supercomputers offer the opportunity to run the same simulation scenario multiple times with varying input parameters which yields ensembles of results. A good example is the forecast of climate change for the next 50 years based on slightly differing assumptions. Additionally, each individual time step of one of those simulation runs might produce very huge data results, which cannot be move for external processing or to be stored on file servers in a manageable amount of time. Thus, it is appropriate to process those data immediately on the supercomputers to extract important features which are much smaller for subsequent processing. Additionally, we are interested to use ensembles for trend analysis which should also processed immediately in-situ.

This PhD studies should address uncertainty analysis of ensemble data while it is simulated on massive-parallel HPC systems. Research topics could include:

• managing simulations on HPC clusters for a co-processing of ensemble simulations
• investigating uncertainty analysis in ensemble simulations
• incorporating topology-based approaches for in-situ multi-resolution data processing
• streaming extracted features progressively to visualization frontend systems for scientific data visualization
• integrating approaches to combine visual analytics approaches with in-situ co-processing
• investigating visualization approaches to present uncertainty with 3D and 4D data visualization
• integrating interactive information visualization for linking and brushing with the scientific uncertainty visualization

If you enjoy software research and want to become part of our team, we are looking forward to receiving your application. We are looking for highly motivated colleagues who identify with their work and inspire others. We also offer the opportunity to contribute your own ideas and to initiate new projects on your own responsibility. You will be expected to present your work at international conferences and in scientific journals. We offer an exciting, friendly, and flexible working environment, where part-time employment is also possible.