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the molecular pathways of disease and to establish the mechanism of action of our therapeutics. The successful candidate will work with our team to analyze multi-level biomarker data generated from pre-clinical
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perturbation technology, AI/ML model development, or advanced molecular biology Experience in single-cell omics, spatial transcriptomics, and/or high-content imaging data analysis Demonstrated record
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screens through analysis of imaging (e.g CellPainting) and spatial-omics data Leverage data to build predictive models of cellular response which can be validated experimentally Who You Are: Ph.D. in
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: Experience with scRNA-seq and flow cytometry for immune cell profiling. Genome Engineering: Background in using CRISPR for creating disease-relevant cell models. - Data Analysis: Familiarity with
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teams. The Opportunity: Opportunity to work closely with computational colleagues to analyze, evaluate, and perform integrative computational analyses. Leverage multimodal high dimensional data to explore
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questions of key importance to the application of human genetics in drug discovery. The wealth of data available within Genentech means we are well-positioned to address a number of critical and impactful
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author paper published or accepted in a well-recognized peer-reviewed journal More information about Man-Wah Tan’s Lab and recent publications: https://www.gene.com/scientists/our-scientists/man-wah-tan
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, spatial data, and perturbation screens with high content molecular and imaging data to understand cellular and multi cellular combinatorial programs in cells and tissues in health and disease. You will join
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mammalian cell culture is preferred. Experience with or strong interest in learning computational structural biology approaches or cryo-ET is a plus. For information about the Deshpande Lab at Genentech
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this data to build predictive models of cell circuits using computational tools including ML/AI. This position will collaborate extensively with scientists in other departments in particular Computational