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City of Hope
Monrovia, CA (In Person)
$74,953 Salary, Full-Time
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Job Description
Learn More City of Hope $34.25 - $37.82 / hr United States, California, Monrovia Apr 23, 2026 Join the forefront of groundbreaking research at City of Hope where we are changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine through cutting-edge research. The Beckman Research Institute of City of Hope invites applications for an outstanding and highly motivated Postdoctoral Fellow to join Dr. Zhaohui Gu's laboratory. The Gu laboratory studies the molecular basis of high-risk B-cell acute lymphoblastic leukemia and related hematologic malignancies through integrated computational and experimental approaches, including cancer genomics, transcriptomics, epigenomics, single-cell analysis, and functional validation in model systems. This position is intended for candidates with advanced training in computational biology, genomics, cancer biology, or a closely related field, and offers the opportunity to contribute to translational research that advances mechanistic understanding and therapeutic discovery. For more information about Dr. Zhaohui Gu's lab, please visit: https://gu-lab.
net and https:
//www.cityofhope.org/Zhaohui-Gu As a successful candidate, you will: Conduct independent and collaborative research in leukemia genomics, transcriptomics, and functional genomics, with emphasis on high-risk B-cell acute lymphoblastic leukemia and related hematologic malignancies. Develop and apply advanced computational and statistical methods to analyze large-scale genomic datasets, including bulk RNA-seq, single-cell RNA-seq, DNA sequencing, epigenomic profiling, and related multi-omics assays. Design, implement, optimize, and document reproducible bioinformatics workflows for high-throughput sequencing data processing, quality control, integrative analysis, and biological interpretation. Integrate genomic, transcriptomic, epigenomic, and clinical data to identify pathogenic mechanisms, subtype-defining biomarkers, and candidate therapeutic targets. Collaborate closely with wet-lab investigators to support experimental design, functional validation, and mechanistic studies of leukemia development, clonal evolution, and treatment response. Contribute to the development of analytical frameworks for translational cancer research, including classification, biomarker discovery, and interpretation of disease-associated genomic alterations. Prepare manuscripts for peer-reviewed journals, present findings at scientific meetings, and contribute to a rigorous and collaborative research environment. Maintain detailed and reproducible records of analytical methods, code, and results in accordance with best practices for scientific rigor and data integrity.Qualifications Your qualifications should include:
- Ph.D. in Biology with quantitative or biomedical emphasis, bioinformatics, genomics, or a closely related quantitative or biomedical discipline.
- Advanced training in one or more of the following areas: cancer genomics, leukemia biology, transcriptomics, translational bioinformatics, functional genomics, epigenomics, single-cell genomics, machine learning for biological data, or computational analysis of high-throughput sequencing datasets.
- Demonstrated record of peer-reviewed research publications, including first-author or major-contributor publications in respected journals in genomics, cancer research, biotechnology, computational biology, or related fields.
- Strong expertise in analysis of next-generation sequencing data, with experience in at least several of the following: bulk RNA-seq, single-cell RNA-seq, DNA-seq, Ribo-seq, ATAC-seq, ChIP-seq, variant analysis, pathway analysis, or integrative multi-omics analysis.
- Advanced programming and workflow development skills in Python, R, Bash, and related computational tools for large-scale data analysis and reproducible research.
- Experience with workflow and software environments relevant to modern genomics research, such as Snakemake, Docker, HPC systems, cloud computing platforms, machine learning libraries, or statistical modeling frameworks.
- Strong understanding of molecular biology, genetics, and cancer biology sufficient to interpret genomic findings in the context of disease mechanisms and experimental design.
- Excellent written and oral communication skills, including the ability to prepare manuscripts, present data clearly, and work effectively in a multidisciplinary research team.
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