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of bioinformatics and computational analysis. To learn more about the Dey Lab, please visit the link below: https://www.gene.com/scientists/our-scientists/anwesha-dey The expected salary range for this position based
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analysis. Experience with spatial assays and/or clinical data is preferred but not required. ● You have experience with in vivo or in vitro models, preferentially relevant to lung biology. ● Excellent
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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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immunotherapy with graph neural networks trained on spatial single-cell tumor microenvironment (TME) data from non-small cell lung cancer (NSCLC). Using high-dimensional datasets, you will learn bi-directional
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laboratory experiments Working knowledge of biochemical techniques is a plus. For information about the Vucic lab at Genentech, please go to: https://www.gene.com/scientists/our-scientists/domagoj-vucic https
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teams. To learn more about the Lill Lab, please visit: https://www.gene.com/scientists/our-scientists/jennie-lill To learn more about the Dey Lab, please visit https://www.gene.com/scientists/our
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collaborative and multidisciplinary environment. Previous experience with proteomics is not required. To learn more about the Ori Lab, please see link below: https://www.gene.com/scientists/our-scientists
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synthetic chemistry and reaction optimization. A working knowledge of molecular biology and/or protein generation. For information about the (lab) at Genentech and publications, please go to: https
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challenges, including data analysis, hypothesis generation, and experimental design optimization. We seek a highly motivated postdoctoral candidate with expertise in AI, machine learning, and computational
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, attribution packages: shap, captum, etc. Experience with bulk and/or single-cell omics data analysis (e.g. bulk genomics and transcriptomics, single-cell RNA-seq, Perturb-seq) Demonstrated ability to clearly