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Join us as we translate today's discoveries into tomorrow's medicine! The Coleman Lab at Cedars-Sinai focuses on developing artificial intelligence (AI)-based tools to uncover the biological mechanisms underlying complex human diseases. Our research employs multimodal approaches that integrate various types of spatial molecular and imaging data to gain deeper insights into disease processes and improve predictive modeling. We are seeking a research data scientist with expertise in deep learning for biomedical applications to join our lab. This fully funded position focuses on developing novel multimodal methods for spatial omics analysis. There will be a focus on leveraging spatially resolved biological data, including spatial omics, tissue histology, and magnetic resonance imaging (MRI) to drive advancements in precision oncology. The ideal candidate will have experience in computational biology and biomedical image analysis. Experience with training deep learning models using self-supervised learning on large-scale datasets is also preferred.
