Automated source finding in astronomical maps @ SKA and NEANIAS

CAESAR (Compact and Extended Source Automated Recognition) is a tool for automated source finding in astronomical maps. It allows to extract and parametrize both compact and extended sources from astronomical radio interferometric maps. The processing pipeline is a series of stages that can run on multiple cores and processors.

The internship aims to port the CAESAR software to cloud infrastructures (VMs and containers) adopted in the NEANIAS project for accessing and processing data through CAESAR and REST-API interface, exposing the services to users also through a usable graphical interface.

IT technologies used: Python, REST-ful API framework (Flask, https://flask.palletsprojects.com/en/1.1.x/#), Kubernetes (https://kubernetes.io/), Docker (https://www.docker.com/), Django (https://www.djangoproject.com/).