The University of Texas MD Anderson Cancer Center is looking to computationally analyze spatial single-cell transcriptomic and proteomic data from patient tumors to identify cellular niches, characterize cell states, model cell-cell communication, and uncover pathways influencing tumor biology.
Requirements
- Build, document, and maintain reproducible analysis pipelines in Python and R for high-dimensional omics datasets.
- Apply analytical methods including clustering, differential expression, trajectory inference, and spatial proximity analyses.
- Integrate multimodal data from platforms such as CosMx, MIBI, STOmics or GeoMx to uncover spatial niches and model cell-cell and host-microbe interactions.
- Process and interpret single-cell RNA-seq and spatial proteomic and transcriptomic datasets to identify cellular states and tumor microenvironment features.
- Conduct pathway enrichment and network-based analyses to identify biologically relevant trends in cancer and immune responses.
- Generate publication-ready visualizations and figures that communicate key findings for manuscripts, grants, and presentations.
- Knowledge of transcriptomics and proteomics is a plus
Responsibilities
- Analyzation and Integration Single-Cell and Spatial Omics Data
- Process and interpret single-cell RNA-seq and spatial proteomic and transcriptomic datasets to identify cellular states and tumor microenvironment features.
- Integrate multimodal data from platforms such as CosMx, MIBI, STOmics or GeoMx to uncover spatial niches and model cell-cell and host-microbe interactions.
- Apply analytical methods including clustering, differential expression, trajectory inference, and spatial proximity analyses.
- Build, document, and maintain reproducible analysis pipelines in Python and R for high-dimensional omics datasets.
- Conduct pathway enrichment and network-based analyses to identify biologically relevant trends in cancer and immune responses.
- Generate publication-ready visualizations and figures that communicate key findings for manuscripts, grants, and presentations.
Other
- Two years experience in scientific software or industry development/analysis.
- Partner with interdisciplinary team members to interpret data, support experimental planning, and contribute to scientific publications.
- Present analytical results in lab meetings and project discussions to inform ongoing research directions.
- Maintain well-organized code, metadata, and supplementary materials to support reproducibility and data sharing.
- Work Location: Hybrid Onsite/Remote
