10 data-"https:" "https:" "https:" "https:" "https:" "J. F" Fellowship positions at Genentech in United States
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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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for analyzing complex mass spectrometric data. Foundational biochemistry skills and an essential understanding of tumor-related biology. Strong interpersonal skills to build effective working relationships across
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data to join the Departments of Proteomics and Genomics Technologies and Neuroscience at Genentech, Inc. We have in-house cutting-edge technologies including proteomics, lipidomics, NGS, CRISPR screens
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field; or a Ph.D. in (Molecular) Biology or Immunology with in-depth experience in high-throughput data analysis evidenced by publications. ● You have experience with single-cell and multi-omic data
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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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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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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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) organization which uses data, by developing best in class computational methods, and applying them to the most relevant scientific problems across all stages of the pipeline. This position is based within
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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