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HomeCompaniesAa067 Sci Rsrch EnPostdoctoral Fellow — Bioinformatics, Cancer Biology and Predictive Biomarkers (Hybrid)

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

Aa067 Sci Rsrch En · United States-California-Duarte · Active · Oracle Taleo Enterprise

Job facts

FieldValue
CompanyAa067 Sci Rsrch En
TitlePostdoctoral Fellow — Bioinformatics, Cancer Biology and Predictive Biomarkers (Hybrid)
Normalized title-
Department / teamDays
LocationDuarte, CA, United States
Work model-
Employment type-
Salary-
Statusactive
ATS providerOracle Taleo Enterprise
Posted / first seen / 2026-05-31
Changed / last seen2026-06-09 / 2026-06-18

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Linked records

CompanyAa067 Sci Rsrch En
Sourcef78e7b35-939f-4bec-9d27-0fe8f2343d0b
ATS providerOracle Taleo Enterprise

Description

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. As a successful candidate you will: 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. 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. As a successful candidate you will: 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. Your qualifications should include: 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). Liquid biopsy experience (ctDNA/cfDNA methylation/CTCs) and knowledge of biomarker validation frameworks preferred. 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). Experience with longitudinal designs, batch correction, and multimodal integration is valued; ML for classification/response prediction is a plus. Scholarly record and collaboration First-author publications (or preprints) and clear communication skills to work with wet-lab biologists, clinicians, and computational scientists. City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about our Comprehensive Benefits, please CLICK HERE . #PD Your qualifications should include: 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). Liquid biopsy experience (ctDNA/cfDNA methylation/CTCs) and knowledge of biomarker validation frameworks preferred. 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). Experience with longitudinal designs, batch correction, and multimodal integration is valued; ML for classification/response prediction is a plus. Scholarly record and collaboration First-author publications (or preprints) and clear communication skills to work with wet-lab biologists, clinicians, and computational scientists. City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about our Comprehensive Benefits, please CLICK HERE . #PD

Full job record

Job IDabf8e7277f384794982c95f8548d88746c308db3
Org ID23a7cd11-5129-4d0d-8086-8a34956f4b37
Source IDf78e7b35-939f-4bec-9d27-0fe8f2343d0b
Board IDf78e7b35-939f-4bec-9d27-0fe8f2343d0b
Provideroracle_taleo
Provider Job Key239446
TitlePostdoctoral Fellow — Bioinformatics, Cancer Biology and Predictive Biomarkers (Hybrid)
Normalized Title
Statusactive
Activeyes
Location TextUnited States-California-Duarte
DepartmentDays
Team
Employment Type
Workplace Type
Remote Policy
CountryUnited States
RegionCA
CityDuarte
Salary RawJoin 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. As a successful candidate you will: 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. 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. As a successful candidate you will: 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. Your qualifications should include: 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). Liquid biopsy experience (ctDNA/cfDNA methylation/CTCs) and knowledge of biomarker validation frameworks preferred. 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). Experience with longitudinal designs, batch correction, and multimodal integration is valued; ML for classification/response prediction is a plus. Scholarly record and collaboration First-author publications (or preprints) and clear communication skills to work with wet-lab biologists, clinicians, and computational scientists. City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about our Comprehensive Benefits, please CLICK HERE . #PD Your qualifications should include: 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). Liquid biopsy experience (ctDNA/cfDNA methylation/CTCs) and knowledge of biomarker validation frameworks preferred. 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). Experience with longitudinal designs, batch correction, and multimodal integration is valued; ML for classification/response prediction is a plus. Scholarly record and collaboration First-author publications (or preprints) and clear communication skills to work with wet-lab biologists, clinicians, and computational scientists. City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about our Comprehensive Benefits, please CLICK HERE . #PD
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