We are seeking a motivated student with a background in computer science, artificial intelligence, applied mathematics or equivalent areas, to help develop and integrate geospatial foundation models with multimodal and multi-resolution satellite imagery for a range of detection, segmentation, and classification tasks. In this role, you will explore the use of state-of-the-art foundation models that leverage geographic, spectral, and temporal information to unlock the full potential of satellite data. This may involve fusing data from different sensor modalities, working with high and low-resolution imagery, and designing novel architectures that can effectively process and extract insights from these complex, multi-scale datasets. You will have the opportunity to apply your skills in areas such as land use mapping and environmental monitoring. 
Strong backgrounds in machine learning, computer vision, and geospatial analysis are highly desirable, as is familiarity with remote sensing data and tools.