Cancer Biology Omics Associate Data Scientist

Summary

The Associate Data Scientist's primary responsibility will be to 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 cell-cell communication, and uncovering pathways through which host-microbe interactions influence tumor biology.

The ideal candidate will have experience in cancer biology omics.

At MD Anderson, we offer careers built on care, growth, and balance. Our employees enjoy a benefits package designed to support every stage of life, starting on day one.
• Paid employee medical benefits (zero premium) starting on first day for employees who work 30 or more hours per week
• Group Dental, Vision, Life, AD&D and Disability coverage
• Paid time off (PTO) and Extended Illness Bank (EIB) paid leave accruals
• Paid institutional holidays, wellness leave, childcare leave, and other paid leave programs
• Tuition Assistance Program after six months of service
• Teachers Retirement System defined-benefit pension plan and two voluntary retirement plans
• Employer paid life, AD&D and an illness-related reduced salary pay program
• Extensive wellness, recognition, fitness, employee health programs and employee resource groups

Key Functions

1. 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.

2. Computational Pipelines for Biological Insight Development

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.

3. Collaborate, Communicate, and Document Research Outputs

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.

Education

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

Experience

Required: Two years experience in scientific software or industry development/analysis.

Preferred: Knowledge of transcriptomics and proteomics is a plus

The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition.

This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.