Research Assistant – Gaia Variable Star Machine Learning

The Department of Physics and Astronomy is seeking a temporary Research Assistant to support the CAS Seed Program project 'Gaia in Technicolor: A Novel Approach for Mapping the Variability of Stars through H-R Diagram Motions'. The role involves using machine learning and functional data analysis to classify millions of variable stars from their motions through the Hertzsprung-Russell diagram in European Space Agency Gaia DR3 multi-epoch photometry. The Research Assistant will serve as the primary day-to-day researcher during the discovery, characterization, and dissemination phases of the project.