57 parallel-processing-bioinformatics-"Multiple" Postdoctoral positions at Stanford University
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analysis of multiple disease-specific datasets and contribute to the development of novel methodologies in this space. The ideal applicant will have a strong background in bioinformatics methods and a keen
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transplantation and viral immunity. Apply and expand expertise in advanced methodologies such as CyTOF, sequencing approaches (CITE-Seq, NGS, RNA-seq), and bioinformatics, with opportunities to learn and integrate
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genetic variation (Lee et al., bioRxiv 2025). This project will expand on this work by generating additional patient-derived models, performing comprehensive differentiation studies across multiple cellular
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-derived models, performing comprehensive differentiation studies across multiple cellular contexts, and using CRISPR activation and interference to identify specific genes that contribute to disease
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bioinformatics, will find this an ideal environment to apply and develop their skills. Duties involve culture and maintenance of stem cells and human/mouse islets, standard molecular biology techniques in DNA and
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, single cell sequencing, and RNA-seq. Knowledge in bioinformatics for the analysis of sequencing data is preferred. The intent of these studies is to determine the immunogenicity of tumor associated
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, single cell sequencing, and RNA-seq. Knowledge in bioinformatics for the analysis of sequencing data is preferred. The intent of these studies is to determine the immunogenicity of tumor associated
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Centers: Otolaryngology, Head & Neck Surgery Appointment Start Date: Applications will be reviewed on a rolling basis until the positions are filled. The start date is flexible. Group or Departmental
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are advancing in the review process. Does this position pay above the required minimum?: Yes. The expected base pay range for this position is listed in Pay Range field. The pay offered to the selected
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intelligence as applied to trauma systems and acute care surgery. Fellows will engage in cutting-edge research spanning multiple domains, including risk prediction models for surgical complications, clinical