This PhD position calls for research into “foundation models,” a type of deep learning neural network. These models, trained using vast amounts of data, serve as starting points for various tasks including, but not limited to, classification, regression, segmentation, and detection. However, the application of these models to the understanding of 3D scenes presents a challenge due to the unique characteristics of the training data. The proposed research aims to bridge this gap. The PhD candidate will primarily be tasked with exploring and constructing innovative vision algorithms rooted in deep learning and based on foundation models. The goal is to develop algorithms that can be effectively and flexibly utilised across diverse data types and domains.