Our group focuses on understanding the cloudy atmospheres of gas giant planets. We want to know what the clouds of these planets consist of, how they cover their home planet, and how they evolve. Relatedly, we are interested in the multi-dimensional atmospheric structure of giant planets, and how circulation may mix chemical species through their atmosphere. This is key for obtaining a robust atmospheric composition and for subsequently constraining a planet’s formation, which may leave characteristic compositional fingerprints. We run atmospheric retrieval and climate modeling codes, using software largely developed and maintained in our group. We compare our predictions to the world’s most sensitive instruments on the ground and in space, including JWST, HST, VLTI-GRAVITY and CRIRES.
The successful candidate (m/f/d) will be engaged in the development of atmospheric models for variable self-luminous planets and brown dwarfs. This role involves working on mostly retrieval, but also climate models, aimed at piecing together a comprehensive understanding of the factors influencing the variability observed in these objects.
Prospective candidates should hold a Ph.D. in astronomy, astrophysics, or a closely related discipline. Applicants should have experience in atmospheric modeling and/or radiative transfer. Proficiency in programming languages such as Python, as well as a compiled language like C, C++, or Fortran, is essential. Familiarity with numerical methods and a background in high-performance computing would be advantageous.