PhD Project: Foundation Models for Automotive Imaging Radar

This PhD project investigates foundation models for automotive imaging radar to learn general representations from largely unlabelled data that generalize across different sensor configurations. The research focuses on transferring representations from vision and LiDAR models to radar, developing multimodal foundation models, and exploring generative or predictive modeling of dynamic radar scenes. The role combines methodological machine learning research with experiments on real automotive sensor data, with opportunities to publish at leading international venues.