Postdoctoral Fellow - Cancer Biology & Multi-Omics Analysis

Postdoctoral Associate
- Cancer Bioinformatics, Biostatistics, and Multi-Omics

• Home
• Explore Careers
• Benefits
• Job Seeker Resources
• Connect With Us

Log In

Dr. Putluri’s laboratory at Baylor College of Medicine is seeking a highly motivated and talented Postdoctoral Fellow in Cancer Bioinformatics, Cancer biology, and Biostatistics to join our multidisciplinary cancer research team.
The Postdoctoral Associate will have strong, hands-on expertise in R and Python and be highly proficient in using R for statistical analysis, bioinformatics, data visualization, and multi-omics data analysis. The candidate should be comfortable independently developing, executing, troubleshooting, and documenting computational workflows for large-scale biological datasets. The Postdoctoral Associate will lead computational and statistical analyses of high-dimensional multi-omics and spatial datasets generated from cancer models and translational human specimens.

The position will focus on developing and applying innovative computational approaches to understand molecular mechanisms of cancer progression, metabolic reprogramming, therapeutic resistance, and tumor–immune interactions.
The Postdoctoral Associate will work with diverse datasets that includes bulk RNA-seq, single-cell RNA-seq, proteomics, metabolomics, ATAC-seq, ChIP-seq, spatial transcriptomics, spatial proteomics, spatial metabolomics and imaging mass cytometry (CyTOF). A major emphasis will be placed on multi-omics data integration, statistical modeling, biomarker discovery, pathway/network analysis, and development of reproducible computational workflows.
This position provides an excellent opportunity to work at the interface of cancer biology, computational biology, bioinformatics, and biostatistics, with access to state-of-the-art multi-omics technologies, patient-derived models, 3D cancer models, and clinically annotated human specimens.
The Postdoctoral Associate will work on cutting-edge translational cancer research projects involving tumor cell signaling, metabolic reprogramming, immuno-oncology, and therapeutic target identification. The lab focuses on understanding metabolic and molecular vulnerabilities driving cancer progression, therapeutic resistance, and tumor–immune interactions. This position offers opportunities to work with cutting-edge cancer models, 3D culture systems, and translational human samples. This position offers the opportunity to work with state-of-the-art platforms that includes patient-derived models (PDXs), 3D organoids/spheroids, advanced molecular assays, and multi-omics datasets.

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

• Develops, implements, and maintains reproducible bioinformatics pipelines for large-scale cancer genomics, transcriptomics, proteomics, metabolomics, epigenomics, and spatial datasets.
• Analyzes bulk RNA-seq data, including quality control, normalization, differential expression, pathway enrichment, gene-set enrichment analysis (GSEA), and molecular signature development.
• Analyzes single-cell RNA-seq datasets that includes quality control, dimensionality reduction, clustering, cell-type annotation, differential expression, cell-state analysis, trajectory analysis, and cell–cell communication.
• Performs computational analysis of spatial transcriptomics data, including spatially variable features, spatial clustering, cell-type…