Lead a team in Bioinformatics & Genomics reporting to Bioinformatics & Genomics leadership
Build data-to-knowledge (D2K) pipelines and integrate GenAI-enabled knowledge workflows
Lead projects in target identification/validation and biomarker strategy by mining and integrating large multi-omics datasets (e.g., TCGA, AC-ICAM, TARGET, GTEx, cBioPortal, dbGaP) with Kite clinical, in vivo and in vitro data
Perform and review high-dimensional analyses (bulk/scRNA-seq/scTCR, spatial transcriptomics, Olink proteomics, metabolomics, flow cytometry, and digital pathology) to characterize the tumor microenvironment and enable molecular phenotyping
Develop predictive models from complex high-dimensional research and clinical datasets linked to differential outcomes (efficacy, durability, CRS/ICANS)
Work closely with cross-functional teams (discovery research, clinical development, translational medicine, regulatory, CMC analytics, IT/Data Engineering, product development) to align analysis plans to program decision points
Coordinate deliverables with clinicians, immunologists, molecular biologists, biostatistics, IT/Data Engineering, commercial and other departments; contribute to protocols, SAPs, CSRs, publications, and Health Authority responses
Requirements
Doctorate and 8 years of scientific experience OR Master’s and 10 years of scientific experience OR Bachelor’s and 12 years of scientific experience
Ph.D. in Bioinformatics, Computational Biology, Immunology, or a closely related field and 5+ years of post-doctoral or industry experience (preferred)
Full proficiency in R and/or Python
Experience in Linux environments and cloud computing (AWS/Azure/GCP)
Development of statistical methods and algorithms
Proficiency building and maintaining large-scale analysis pipelines (containers, workflow orchestration, CI/CD)
Operating securely in the cloud
Deep knowledge of cancer biology and cancer immunology; familiarity with cell-therapy translational datasets and safety/efficacy biomarkers (CRS/ICANS)
Hands-on experience with bioinformatics analysis of NGS and flow cytometry
Analysis of bulk and single-cell transcriptomics and spatial data using standard pipelines
Strong understanding of statistics and ability to generate robust predictive models for multidimensional data
Excellent interpersonal, verbal and written communication skills
Experience in cancer immunology research as substantiated by first or senior authorship in leading journals
Team leadership and people management experience (preferred)
Benefits
discretionary annual bonus
discretionary stock-based long-term incentives (eligibility may vary based on role)
paid time off
company-sponsored medical insurance
company-sponsored dental insurance
company-sponsored vision insurance
company-sponsored life insurance
benefits package (additional details at https://www.gilead.com/careers/compensation-benefits-and-wellbeing)
Applicant Tracking System Keywords
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