|Main supervisor||S.Förster (email@example.com)|
|Local supervisor 1||tbd|
|Local supervisor 2||–|
|Local supervisor 3||–|
|Local supervisor 4||–|
|Title||Towards Polarization Analysis for Quasi Elastic Neutron Scattering (PA-QENS)|
|Description||High-throughput SANS instruments such as KWS-1 and KWS-2 produce 2D-SANS images at high rate. The SANS-patterns may be complex such that a detailed data analysis will only be possible after the experiments.
The project will develop a machine-learning based software that recognizes and classifies a large number of classes of the most common structures with their isotropic and anisotropic SANS-patterns. After classification, the software will further allow to model the data with 2D- or 1D-fits using GPUs for rapid calculations. The project will be conducted with XENOCS, a company that sells X-ray equipment where a large number of small-angle data have to be analyzed.
Students will become familiar with the software development and machine learning tools, and develop a modern portfolio of skills in both academic and industrial settings.