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. PyTorch, Jax, scikit-learn) applied to genomic datasets Experience with various sequence modeling architectures and interpretable AI methods (attribution methods including SHAP, Integrated Gradients, etc
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—including next-generation sequencing, single-cell approaches, genome engineering, and spatial biology—to study mechanisms of tumor initiation and progression. Collaborate across disciplines to translate basic
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discovery. This position in particular focuses on sequence-to-function deep genomics modeling, with the goal of developing performant models that make generalizable out-of-distribution predictions
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structural biology to tackle challenging scientific questions. Your responsibilities will include, but are not limited to: Multi-omics analysis of bulk and single-cell sequencing data. Developing deep learning
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that combine the engineering and analytical principles of multiple scientific disciplines. We are seeking a talented postdoctoral fellow to join our team and advance our mission by contributing to the discovery
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to groundbreaking research that aligns with Genentech strategic ambitions. The postdoc program is designed to empower recent Ph.D. graduates to conduct world-class research, publish in top-tier journals, and build a
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yourself completely to groundbreaking research that aligns with Genentech’s strategic ambitions. The program is meticulously designed to empower recent Ph.D. graduates to conduct world-class research
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funded research expenses, you can dedicate yourself to groundbreaking research that aligns with Genentech strategic ambitions. The Genentech Postdoc Program provides access to world-class seminars
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that aligns with Genentech strategic ambitions. The postdoc program is designed to empower recent Ph.D. graduates to conduct world-class research, publish in top-tier journals, and build a robust scientific
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research that aligns with Genentech strategic ambitions. The postdoc program is designed to empower recent Ph.D. graduates to conduct world-class research, publish in top-tier journals, and build a robust