Universität Bern is seeking a researcher to contribute to the IN/AT‑SYNC JWST project focusing on sub-Neptune atmospheres. The ideal candidate should be proficient in Bayesian statistical methods and have experience with exoplanetary transits and atmospheric physics. The role
Joint project between – Pertz Lab () & D. Ginsbourgers Group () We are seeking highly qualified, motivated and creative candidates wishing to join a collaborative project at the interface of statistical machine learning and live-cell
PhD Position in Statistics with a focus on Statistical Machine Learning for Self-Driving Microscopy 100% Joint project between – Pertz Lab () & D. Ginsbourgers Group () We are seeking highly qualified, motivated and creative candidates
Your profile The ideal candidate would have expertise in applying Bayesian statistical methods to astronomical datasets, experience modelling exoplanetary transits, deep knowledge of atmospheric physics (e.g. chemistry, radiative transfer, etc.), and a proven track record as an independent
The University of Bern is seeking a PostDoc to apply Bayesian statistical methods to astronomical datasets, particularly focusing on exoplanetary atmospheres. The role includes collaborating on the IN/AT-SYNC JWST project and mentoring students. This position offers competitive salary
UniBE is prestigious. With us, you benefit from the excellent reputation of a long-standing institution all around the world. Your profile The ideal candidate would have expertise in applying Bayesian statistical methods to astronomical datasets, experience modelling exoplanetary
