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multidisciplinary translational neuro-oncology research program focused on immunotherapy, biomarker discovery, and spatial biology. In this role, you will help advance innovative research embedded within investigator
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Contribute to the analysis of single-cell RNA-seq, spatial transcriptomics, and multi-omic datasets Apply computational and machine learning approaches to build mechanistic biological models and rationally
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sequencing, and spatial transcriptomics. Be Bold. Qualifications: A PhD, MD, or MD/PhD in a biomedical sciences-related field is required, along with a peer-reviewed publication record. Experience in RNA
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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell
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will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology