I am building a new research group at Hamburg Observatory focused on the formation of structures in the early Universe, specifically we aim to understand the emergence of quasars - active growing supermassive black holes. In order to expand the quasar redshift frontier and build statistical samples at Cosmic Dawn, we are using wide-area surveys in concert with large ground-based and space-borne observatories to conduct spectroscopic identification campaigns and multi-wavelength follow-up observations. The quasar selection strategies employ machine-learning methods on large astronomical data sets. Follow-up observations are reduced using state-of-the-art astronomical data reduction software and analysed using modern statistical inference techniques.
In this context group members use and are trained in the following skills to conduct their research:
- spectroscopic data reduction
- large-scale data analysis
- machine-learning methods
- robust statistical inference techniques
- software development (Python 3)