Translational Cancer Multi-Omics Bioinformatics Postdoc

Baylor College of Medicine (BCM); Houston (TX); On-site; USD 52,000 - 70,000; Full time

Job summary

Baylor College of Medicine in Houston is seeking a Postdoctoral Fellow to lead computational analyses across cancer bioinformatics, bio-statistics, and biology projects. The role focuses on multi-omics integration, biomarker discovery, and advanced statistical modeling using high-dimensional datasets from patient-derived models and human specimens.

The fellow will work with RNA-seq, single-cell, proteomics, metabolomics, spatial omics, and imaging mass cytometry, developing reproducible

Qualifications

• PhD required or equivalent in a quantitative field.
• Strong programming skills in R and/or Python.
• Experience with high-throughput omics data (RNA-seq, single-cell, proteomics, etc.).

Responsibilities

• Develops, implements, and maintains reproducible bioinformatics pipelines for multi-omics datasets.
• Analyzes bulk and single-cell RNA-seq data, and performs differential expression and pathway analysis.
• Performs multi-omics data integration and biomarker discovery.
• Conducts computational analyses of spatial omics data and imaging mass cytometry.
• Develops machine learning models for biomarker discovery and patient stratification.
• Contributes to manuscript preparation and grant submissions.
• Mentors students and collaborates with wet-lab researchers.

Skills

Bioinformatics

Python

R

Machine Learning

Education

PhD in Bioinformatics, Computational Biology, Biostatistics, Statistics, Biomedical Informatics, Data Science, or related quantitative field

Tools

Linux/Unix

Git

Job description

Baylor College of Medicine in Houston is seeking a Postdoctoral Fellow to lead computational analyses across cancer bioinformatics, bio-statistics, and biology projects. The role focuses on multi-omics integration, biomarker discovery, and advanced statistical modeling using high-dimensional datasets from patient-derived models and human specimens.

The fellow will work with RNA-seq, single-cell, proteomics, metabolomics, spatial omics, and imaging mass cytometry, developing reproducible