Postdoctoral Fellow — Bioinformatics, Cancer Biology and Predictive Biomarkers (Hybrid)

City of Hope • Duarte, CA

4d • Hybrid

About The Position

Join the forefront of groundbreaking research at City of Hope where we're 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 Bild Laboratory at City of Hope uses systems biology to understand how tumors evolve under therapy, uncover resistance mechanisms, and identify actionable vulnerabilities. We integrate longitudinal patient cohorts with single-cell and bulk multi-omics, liquid biopsy, and patient-derived models, partnering closely with clinicians at an NCI-designated Comprehensive Cancer Center.
We seek a Postdoctoral Research Fellow (bioinformatics) to lead analysis of large, longitudinal multi-omic datasets from cancer patients on therapy. You will build scalable pipelines across data types and translate results into biomarker discovery, downstream modeling, and clinical interpretation.
This role fits a scientist who enjoys hands-on cohort processing and harmonization and wants analyses to directly inform how tumors evade treatment. You will collaborate with computational scientists developing predictive models, contributing genomic analysis, workflow engineering, biological interpretation, and (when appropriate) machine-learning methods.
Learn more about Dr. Bild’s lab here.

Requirements

• PhD (or equivalent) in bioinformatics, computational biology, genomics, systems biology, biomedical engineering, statistics, computer science, or a related quantitative field (completed within five years or expected within six months).
• Demonstrated expertise across most of the following areas: Cancer biology and genomics domain knowledge
• Working understanding of cancer biology and signaling, and how DNA mutation/methylation affects RNA and protein.
• Familiarity with standard cancer-genomics analyses (somatic calling, CNV/SV, mutational signatures, purity/ploidy, clonal structure).
• Bioinformatics and computational skills
• Proven ability to process large-scale sequencing data end-to-end and build reproducible workflows on HPC and/or cloud (AWS/GCP/Azure).
• Proficiency with R/Bioconductor and Python, git, containers (Docker/Singularity), and core genomics formats (BAM/CRAM, VCF, MAF).
• Familiarity with common aligners/callers and single-cell toolchains (e.g., BWA/STAR, Mutect2, Seurat/Scanpy) is expected.
• Statistics and data analysis
• Strong applied statistics for genomic data (multiple testing, multivariate methods, dimensionality reduction, differential expression/methylation, survival analysis).
• First-author publications (or preprints) and clear communication skills to work with wet-lab biologists, clinicians, and computational scientists.

Nice To Haves

• Liquid biopsy experience (ctDNA/cfDNA methylation/CTCs) and knowledge of biomarker validation frameworks preferred.
• Experience with longitudinal designs, batch correction, and multimodal integration is valued; ML for classification/response prediction is a plus.

Responsibilities

• Build reproducible pipelines for serial tumor and liquid-biopsy data across large cohorts.
• Analyze somatic variation (SNV/indel, CNV/SV), methylation, and deconvolution in longitudinal ctDNA and tissue.
• Integrate bulk and single-cell RNA-seq with genomic/epigenomic data to define tumor states, microenvironment, and resistance programs.
• Co-develop and validate drug-response biomarkers with computational, experimental, and clinical teams.
• Publish and present results, mentor trainees, and grow an independent research direction.

Benefits

• Comprehensive Benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree