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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 analyse their results.

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The scientific objectives of the two PhD projects are to study, in the framework of the CHEOPS mission and the future PLATO mission (launch in early 2027), the internal structure of planets and the architecture of planetary system. The work will be based on population synthesis models of planetary system formation developed in our group, as well as generative AI based formation models. Frequent interactions with members of ...