PhD positions in planetary science and machine learning

We are looking for two 4‑year PhD candidates in planetary science and machine learning at the University of Bern.

• Bachelor’s and master’s degrees in physics, astrophysics, planetary science or a related field.
• Experience with data analysis, ML and AI methods is an advantage.
• Enthusiastic, persistent, communicative and willing to integrate into the teams in Bern and the Swiss landscape (TAPS, CSH and SIPS).

Work will consist of numerical modelling of the physics of planetary system formation and development of ML and AI methods to analyse simulation results. You will conduct population synthesis modelling, develop generative AI based formation models, and collaborate with the CHEOPS and PLATO missions and associated consortia.

• Annual gross salary of 50'042 Swiss francs for full‑time employment (including a 13th month salary).
• Child allowance, maternity and paternity leave.
• Participation in group meetings, journal clubs, research discussions, seminars and conferences, both in Bern and at SIPS.
• Strong research infrastructure and an international network.
• Healthy corporate culture and a supportive work environment.

Position type: 100 % fixed‑term (4 years) with a standard first‑year probation period. Expected start date: 1 September 2026 (negotiable).

The University of Bern is an equal opportunity employer and particularly encourages applications from female researchers.

To apply , send a one‑page letter of motivation, a one‑page covering letter, a curriculum vitae (max. 2 pages), a list of publications (if applicable), undergraduate and graduate transcripts, and evidence of at least 1‑2 letters of recommendation to yann.alibert with the subject line “2 PhD positions in planetary science and machine learning”. The complete application should be submitted as a single PDF file no later than 15 June 2026.

Interviews for shortlisted candidates will take place online during the first half of July 2026.