Postdoctoral Associate - Specialist - Cancer Genomics

Baylor College of Medicine; Texas; On-site; USD 70,000 - 75,000; Full time

Job summary

Baylor College of Medicine in Houston, TX invites applications for a Postdoctoral Associate - Specialist in Cancer Genomics. The successful candidate will analyze and interpret large-scale leukemia genomic and multiomic data, focusing on WGS, WTS, methylation, long-read sequencing, ATAC-seq, HiChIP, and single-cell data.

Responsibilities include training or mentoring students, validating classifiers, and integrating sequencing data with clinical covariates to produce reproducible outputs.

Qualifications

• Ph.D. in a quantitative field relevant to cancer genomics.
• Experience with WGS/WTS, RNA-Seq, DNA methylation, ATAC-Seq, HiChIP preferred.
• Strong programming and data-interpretation skills.

Responsibilities

• Analyze genomic and multiomic data from pediatric leukemia studies.
• Perform variant interpretation, fusion/gene-expression analyses, and methylation analysis.
• Support validation of multiomic classifiers and risk models with rigorous documentation.
• Coordinate QC, reproducible workflows, and collaboration with bioinformatics teams.
• Prepare data summaries, figures, and manuscripts for collaborative projects.
• Lead long-read sequencing and methylation analyses with integration to transcriptomic data.
• Manage regulatory-state and relapse-biology analyses across datasets.
• Other duties as assigned.

Skills

Genomic data analysis

Multiomic integration

Pediatric cancer genomics

Education

Ph.D. in Computational Biology/Bioinformatics

Tools

R

Linux/HPC

Git

Job description

Postdoctoral Associate - Specialist - Cancer Genomics

Division: Pediatrics

Work Arrangement: Onsite only

Location: Houston, TX

Salary Range: $70,000 - $75,000

FLSA Status: Exempt

Work Schedule: Monday - Friday, 8 a.m. - 5 p.m.

Summary

The Postdoctoral Associate - Specialist will analyze and interpret large-scale leukemia genomic and multiomic datasets. The role focuses on WGS, WTS, DNA methylation, long-read sequencing, ATAC-seq, HiChIP, and single-cell RNA/ATAC data, with emphasis on variant interpretation, subtype classification, model validation, data harmonization, and reproducible outputs.

The Postdoctoral Associate will train or mentor students, or junior analysts as the laboratory grows. Study complexity includes high-dimensional genomic and epigenomic datasets from pediatric leukemia cohorts, external validation cohorts, and Texas Children's cohorts. The role requires integration of sequencing data, clinical covariates, model outputs, and biological interpretation with reproducible documentation.

Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.

Job Duties

• Analyzes and interprets genomic, transcriptomic, epigenomic, long-read, chromatin-accessibility, chromatin-contact, and single-cell datasets from pediatric leukemia studies.
• Performs variant interpretation, structural variant annotation, subtype classification, fusion/gene-expression analysis, methylation analysis, and multiomic integration.
• Supports validation/evaluation of multiomic classifiers and risk models, including benchmarking, performance assessment, and documentation of research-use outputs.
• Participates in testing, documentation, QC review, and implementation of reproducible WGS/WTS and multiomic workflows with the PI and institutional bioinformatics teams.
• Prepares data summaries, figures, reports, manuscripts, and presentations for collaborative research projects.
• Coordinates long-read sequencing and DNA methylation analysis to identify cryptic regulatory and structural variants in pediatric leukemia/lymphoma, that includes breakpoint interpretation, allelic phasing, methylation-aware analysis, and integration with transcriptomic evidence.
• Manages multiomic classifier and risk-model validation that includes evaluation against existing diagnostic workflows, turnaround time, and incremental biomarker yield.
• Manages regulatory-state and relapse-biology analyses integrating scRNAseq, scATAC-seq, bulk ATAC-seq, enhancer-promoter connectivity data, reference atlases, and diagnosis-relapse pairs.
• Coordinates QC review, documentation, and implementation support for WGS/WTS workflows.
• Performs other job-related duties as assigned.

Minimum Qualifications

• Ph.D. in Chemistry, Computational Sciences, Computational Biology, Structural Biology, Computer Science, Bioinformatics, Statistics, or related disciplines. May also include Ph.D. in Biology or Biomedical Sciences in combination with an M.S. or extensive multidisciplinary experience in one of the above quantitative fields.

Preferred Qualifications

• PhD in computational biology, bioinformatics, genomics, statistics, computer science, biomedical sciences with strong quantitative training, or related field.
• Experience in WGS, WTS/RNA-seq, DNA methylation, long-read sequencing, ATAC-seq, HiChIP/chromatin-contact data, scRNA-seq, scATAC-seq, cancer genomics, structural variation, R, Linux/HPC, version control, and reproducible workflows.

Baylor College of Medicine fosters diversity among its students, trainees, faculty, and staff as a prerequisite to accomplishing our institutional mission and setting standards for excellence in training healthcare providers and biomedical scientists, promoting scientific innovation, and providing patient-centered care. Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.