Postdoctoral Fellow: Cancer Bioinformatics & Multi-Omics

Baylor College of Medicine; Houston (TX); On-site; USD 60,000 - 70,000; Full time

Job summary

Baylor College of Medicine is seeking a Postdoctoral Fellow in Cancer Bioinformatics, Cancer Biology, and Biostatistics to join a multidisciplinary team in Houston. The ideal candidate will lead computational analyses of high‑dimensional multi‑omics and spatial datasets, developing reproducible workflows for large‑scale data from cancer models and human specimens.

Strong expertise in R and Python, experience with RNA‑seq, spatial omics, and multi‑omics integration are essential.

Qualifications

• PhD in Bioinformatics, Computational Biology, Biostatistics, Statistics, Biomedical Informatics, Data Science, cancer biology, Genomics, Systems Biology, or related field.
• Strong programming in R and/or Python.
• Experience analyzing high-throughput datasets such as RNA-seq, scRNA-seq, spatial omics, or CyTOF.

Responsibilities

• Develops reproducible bioinformatics pipelines for multi‑omics datasets.
• Analyzes bulk and single‑cell RNA‑seq data with QC and differential expression.
• Performs spatial transcriptomics data analysis and integration with scRNA‑seq.
• Applies ML/statistical modeling for biomarker discovery and patient stratification.
• Prepares manuscripts and presents findings at meetings.
• Maintains computational workflows with documentation and HPC workflows.

Skills

R

Python

Bioinformatics

Biostatistics

Multi-omics

Machine learning

Education

MD or Ph.D. in Basic Science, Health Science, or related field

Ph.D. in Bioinformatics, Computational Biology, Biostatistics, Statistics, Biomedical Informatics, Data Science, cancer biology, Genomics, Systems Biology, or related quantitative field

Tools

Linux/Unix

HPC

GraphPad Prism

Microsoft Excel

Job description

Baylor College of Medicine is seeking a Postdoctoral Fellow in Cancer Bioinformatics, Cancer Biology, and Biostatistics to join a multidisciplinary team in Houston. The ideal candidate will lead computational analyses of high‑dimensional multi‑omics and spatial datasets, developing reproducible workflows for large‑scale data from cancer models and human specimens.

Strong expertise in R and Python, experience with RNA‑seq, spatial omics, and multi‑omics integration are essential.