Research Associate in Machine Learning for Astronomical Imaging (Fixed Term)
Conducts original research in machine learning for astronomical imaging, focusing on detecting and characterising low surface brightness structures in wide-field surveys. Develops novel AI methods—such as generative and simulation-based models—and builds scalable software infrastructure for deployment on GPU and HPC systems. Publishes findings, presents at conferences, and releases open-source tools, while contributing to supervision and collaborative research activities.
Contract