A newly founded junior research group at the German Aerospace Center (DLR) in Berlin will investigate methods from the field of machine learning for the analysis of spectroscopic in situ planetary data. Techniques like laser-induced breakdown spectroscopy (LIBS) or Raman spectroscopy have many advantages for the robotic exploration of extraterrestrial bodies and Mars missions. The recently landed rover Perseverance and its predecessor Curiosity are equipped with such instruments. However, the physics behind these methods is complex, and not all problems can be solved analytically. Therefore, we want to investigate machine learning methods to address the challenging complexity in the data.

The Ph.D. project will include laboratory measurements with highly performant but also compact instrumentation, simulating, for example, martian atmospheric conditions. The focus will be on the classification and identification of geological samples, thus different types of minerals and rocks. We are looking for a motivated and enthusiastic student with expertise in data science and a high interest in solar system exploration.

For more information, please visit https://www.dlr.de/dlr/jobs/en/desktopdefault.aspx/tabid-10596/1003_read-46489/.

We are looking forward to your application!