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Position: Postdoctoral Fellow - Computational Biology and Bioinformatics
Institution: Genentech, Inc.
Location: South San Francisco, California, United States
Duties: Conduct independent research under joint mentorship of Drs. Geiger-Schuller and Corrada-Bravo; Develop novel computational methods for interpretable representation learning of multi-modal combinatorial perturbation data; Collaborate with colleagues in neuroscience on the design and analysis of perturbation studies including the application of methods developed in this project; Publish high-quality papers reporting on methodological and biological advances resulting from this work
Requirements: Ph.D. in Computational Biology, Computer Science, Statistics, Biostatistics or related field; Demonstrated ability to design, implement and apply modern statistical and computational methodology for the analysis of high-throughput genomics data in general (e.g., scRNA-seq, RNA-seq, scATAC-seq, ATAC-seq, CITE-seq, etc.); Expertise implementing statistical and computational methods in appropriate data intensive programming environments: e.g., python, R or Julia
   
Text: Postdoctoral Fellow - Computational Biology and Bioinformatics Conduct independent research under joint mentorship of Drs. Geiger-Schuller and Corrada-Bravo; Develop novel computational methods for interpretable representation learning of multi-modal combinatorial perturbation data; Collaborate with colleagues in neuroscience on the design and analysis of perturbation studies including the application of methods developed in this project; Publish high-quality papers reporting on methodological and biological advances resulting from this work Ph.D. in Computational Biology, Computer Science, Statistics, Biostatistics or related field; Demonstrated ability to design, implement and apply modern statistical and computational methodology for the analysis of high-throughput genomics data in general (e.g., scRNA-seq, RNA-seq, scATAC-seq, ATAC-seq, CITE-seq, etc.); Expertise implementing statistical and computational methods in appropriate data intensive programming environments: e.g., python, R or Julia
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