Cancer Biology Omics Associate Data Scientist

Associate Data Scientist

The Immunology department at MD Anderson Cancer Center seeks to determine the fundamental cellular and molecular mechanisms of a wide range of processes by which the body recognizes and eliminates pathogens and use these findings to unleash the patient's own immune system against previously treatment-resistant cancers. Treating the immune system rather than the cancer itself, the therapeutics developed are applicable to many cancers.

The Associate Data Scientist in the Bullman Lab will assist in the computational analysis of spatial single-cell transcriptomic and proteomic data from patient tumors generated from platforms such as CosMx Spatial Molecular Imager. Analyses will involve identifying spatially localized cellular niches, characterizing immune and epithelial cell states, modeling cellcell communication, and uncovering pathways through which hostmicrobe interactions influence tumor biology.

The ideal candidate brings experience in single-cell or spatial biology, cancer biology omics or genomics, and proficiency in Python, supported by relevant academic training and applied research or industry experience.

Minimum $42.31 Midpoint $52.88 Maximum $63.46 The typical work schedule is onsite. Work location: Texas Medical Center.

Why Us?

Joining MD Anderson means contributing directly to research that shapes the future of cancer treatment while developing deep technical and scientific expertise. This role offers opportunities for collaboration, growth, and meaningful impact within a mission-driven environment that values both innovation and work-life balance.

Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&D, and disability insurance.

Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options.

Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups.

Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs.

Responsibilities

1. Analyze & Integrate Single-Cell and Spatial Omics Data

Process and interpret single-cell RNA-seq, spatial transcriptomic, and spatial proteomic datasets. Apply clustering, differential expression, trajectory inference, and spatial proximity methods. Integrate multimodal datasets from CosMx, MIBI, STOmics, and GeoMx platforms. Identify spatially localized cellular niches and characterize immune and epithelial cell states. Model cellcell interactions and evaluate hostmicrobe influences on tumor biology.

2. Develop Computational Pipelines

Build and maintain reproducible Python and R analysis pipelines. Document workflows and ensure consistency across high-dimensional omics analyses. Conduct pathway enrichment and network analyses to identify relevant biological trends. Generate publication-quality figures for manuscripts, grants, and presentations.

3. Collaborate & Communicate Research Findings

Partner with interdisciplinary team members to interpret data and support experimental planning. Present analytical results in lab meetings and project discussions. Maintain organized code, metadata, and supplementary materials to ensure reproducibility and data sharing.

Education

Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field.

Work Experience

Required: Two years Scientific software or industry development/analysis. Preferred: Must have prior experience in single-cell or spatial biology, cancer biology omics, or cancer genomics, and demonstrate proficiency in Python.