11 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at Genentech
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the Sterne-Weiler Lab i n Computational Biology / Discovery Oncology and co-mentored by the Frey Lab in Prescient Design (Machine Learning for Drug Discovery). The postdoctoral position is focused
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discoveries. Who You Are: Ph.D. with a proven track record of excellence in Computer Science and Machine Learning, with substantial domain experience in biology and genomics. Must have advanced at least one key
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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
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The Position A position is available for a postdoctoral fellow to join the Genentech Computational Sciences (gCS) organization, which develops and applies best in class computational methods
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ATAC sequencing, spatial transcriptomics, proteomics, whole-genome sequencing, functional screens, bioinformatics, and/or data algorithms including machine learning will be given preference. A successful
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-throughput functional screens, and computational biology. They will deploy single cell genomics and spatial transcriptomics approaches to uncover new tumor-TME communication patterns, deploy therapeutic
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applicant will have an opportunity to work closely with a diverse scientific team that includes microbiologists, immunologists, cell biologists and bioinformaticians. Who You Are: Recent PhD in the field
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access to state-of-the-art analytics and a robust cross-functional scientific community. The Opportunity: You will be part of the Genentech post-doctoral training program that provides an outstanding
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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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perturbation methods to address basic research questions and facilitate drug discovery. Goals for this position include the development and application of novel experimental and computational tools for spatial