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Postdoctoral Fellow - AI/ML for Single Cell and Spatial Genomics

Employer
Genentech
Location
South San Francisco
Salary
Competitive
Closing date
22 Apr 2024

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Employer Sector
Scientific
Contract Type
Permanent
Hours
Full Time
Travel
None
Job Type
Artificial Intelligence
The Position We advance science so that we all have more time with the people we love. As a postdoctoral fellow at Genentech, you will join a prestigious community of early career researchers and kickstart your journey toward becoming a scientific leader in biotechnology and biomedical science. With competitive salaries and state-of-the-art technology, you can dedicate yourself to groundbreaking research that aligns with Genentech's strategic ambitions. The Opportunity The Corrada-Bravo (BRAID-Biology Research AI Development) and Geiger-Schuller (Cellular and Tissue Genomic) Labs at Genentech Research and Early Development are looking for an exceptional Postdoctoral Fellow to lead development and application of Machine Learning methods for the representation, analysis and interpretation of spatial transcriptomics data, and the design and interpretation of in-vivo perturbation screens with high-content spatial readouts. This postdoc will be joint with the Corrada-Bravo and Geiger-Schuller labs with co-mentorship from both lab leaders and close collaboration with ongoing efforts in neurodegeneration. Conduct independent research under the joint mentorship of Drs. Geiger-Schuller and Corrada-Bravo Develop and apply novel ML methods for interpretable representation learning of multi-modal data (including spatial transcriptomics and imaging) to assist the design and interpretation of in-vivo perturbation screens with spatial readouts Collaborate with colleagues in neuroscience on the design and analysis of perturbation studies based on the application of methods developed in this project Publish high-quality papers reporting on methodological and biological advances resulting from this work Who you are: Ph.D. in Computational Biology, Computer Science, Statistics, Biostatistics or related field required Demonstrated ability to design, implement, and apply modern ML methods for the analysis of high-throughput genomics data in general (e.g., spatial transcriptomics, scRNA-seq, RNA-seq, scATAC-seq, ATAC-seq, CITE-seq, etc.) required Expertise implementing ML methods using appropriate technologies (e.g, PyTorch, JAX) required Demonstrated ability to effectively communicate complex computational biology problems to peers, users, and leadership required Independent, highly motivated, and highly collaborative with the ability to work together with multi-disciplinary teams of computational scientists and biologists. Learn More About the Labs: Corrada-Bravo Lab: H??ctor Corrada Bravo is the Director and Lead of AI Methods for Functional Genomics in gRED's BRAID (Biology Research AI Development) Department where he leads the BRAID-CSO (Cellular States and their Organization) group. He has extensive experience designing and developing methods and software for the analysis of high-throughput genomics, including epigenetic and single-cell transcriptomic data, with a specific interest in the development of explainable AI and generative modeling methods for applications in Functional Genomics. Prior to joining Genentech in June 2020, he was an Associate Professor at the Center for Bioinformatics and Computational Biology at the University of Maryland in College Park. He holds a Ph.D. in Computer Science from the University of Wisconsin (advised by Grace Wahba) and completed a postdoctoral fellowship in Biostatistics at the Johns Hopkins Bloomberg School of Public Health (mentored by Rafael Irizarry). Geiger-Schuller Lab: Katie Geiger-Schuller is a Senior Scientist in gRED's Cellular and Tissue Genomics group where she develops new multi-modal high content screening technologies and applies them to understand cellular circuits in Neuroscience and tissue microenvironments. She has extensive training in single-cell multi-omic screening, specifically in primary cell systems. Katie enjoys working at the interface of technological and computational development allowing innovations in either space to unlock new questions to better understand disease. Katie holds a PhD in Molecular Biophysics from Johns Hopkins University (advised by Doug Barrick) and completed her postdoctoral fellowship at the Broad Institute (mentored by Aviv Regev). For information about the Postdoctoral Program at Genentech, please go to: Relocation benefits are available for this job posting. The expected salary range for this position based on the primary location of California is $64,800 and $120,300. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for the benefits detailed at the link provided below. Benefits Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.

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