Description
The role develops and optimizes technologies for astronomical data processing to detect transient sources in sky surveys, identify gravitational-wave counterparts, and coordinate follow-up across radio, optical, X-ray, gamma-ray, neutrino, and other multi-messenger domains. It involves Bayesian methods, machine learning, data provenance, radio calibration and imaging, and preparation of science-ready data products from large-area surveys. The position requires a PhD in Astrophysics or an equivalent research field, extensive variability and multiwavelength research experience, and familiarity with radio data processing.
