2 PhD positions in planetary science and machine learning

The ideal candidate will have a bachelor's and master's degree in physics, astrophysics, planetary science or equivalent. Experience with data analysis, ML and AI methods is an advantage. Candidates should be enthusiastic, persistent, communicative and willing to integrate into the teams in Bern and the Swiss landscape (TAPS, CSH and SIPS). The research will consist of a combination of numerical modelling of the physics of planetary system formation and development of ML and AI methods to analys…