Leukemia Multiomics Postdoc: Genomics & Variant Analysis

Women In Science; Houston (TX); On-site; USD 54,000 - 70,000; Full time

Job summary

Baylor College of Medicine in Houston is seeking a Postdoctoral Associate - Specialist to analyze large-scale leukemia genomic and multiomic data, including WGS, RNA-seq, methylation, long-read sequencing, ATAC-seq, and single-cell data. The role emphasizes variant interpretation, subtype classification, model validation, and reproducible outputs.

The incumbent will mentor students and junior analysts, integrate sequencing data with clinical covariates, and document workflows with the PI and

Qualifications

• PhD in a relevant field with strong quantitative training.
• Experience analyzing genomic and multiomic data is preferred.
• Ability to develop and document reproducible workflows.

Responsibilities

• Analyzes genomic, transcriptomic, epigenomic, long-read, and single-cell datasets from pediatric leukemia studies.
• Performs variant interpretation, methylation and multiomic classifier analyses.
• Supports validation of models, benchmarking, and documentation of research outputs.
• Implements reproducible WGS/WTS workflows with bioinformatics teams.
• Prepares data summaries, figures, and manuscripts for collaborative projects.
• Coordinates long-read sequencing and DNA methylation analyses with transcriptomic evidence.

Skills

Genomic data analysis

Multiomic integration

Documentation & reproducibility

Education

Ph.D. in Chemistry, Computational Sciences, Computational Biology, Structural Biology, Computer Science, Bioinformatics, Statistics, or related disciplines

Tools

R

Linux/HPC

Version control

Reproducible workflows

Job description

Baylor College of Medicine in Houston is seeking a Postdoctoral Associate - Specialist to analyze large-scale leukemia genomic and multiomic data, including WGS, RNA-seq, methylation, long-read sequencing, ATAC-seq, and single-cell data. The role emphasizes variant interpretation, subtype classification, model validation, and reproducible outputs.

The incumbent will mentor students and junior analysts, integrate sequencing data with clinical covariates, and document workflows with the PI and