Research Computational Analyst

The primary purpose of the Research Computational Analyst position is to assist with data analysis for genomic and multi-omics studies and help disseminate the statistical methods/software tools and findings in Professor Wenyi Wang's lab in the Department of Bioinformatics and Computational Biology.

The ideal candidate will have strong bioinformatics and computational skills, with experience analyzing genomic and multi-omics datasets and implementing reproducible pipelines using Python, R, and workflow tools on HPC systems. They should be detail-oriented, collaborative, and capable of troubleshooting workflows while maintaining data integrity and clear documentation. Excellent communication skills and the ability to support multidisciplinary research teams are essential.

• 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.

• Assist with the analysis of high-dimensional genomic, transcriptomic, and other molecular datasets (e.g., WGS/WES, RNA-seq, scRNA-seq) in support of ongoing research projects.
• Support data curation and QC, and help run and maintain established workflows for alignment, variant and copy‑number calling, and downstream analyses/visualization.
• Contribute to literature review and interpretation of results by summarizing relevant findings and providing analytical input for follow‑up studies in coordination with the project lead/PI.

• Assist with implementing and maintaining reproducible NGS and multi‑omics pipelines using Python, R, and workflow tools (e.g., Snakemake, Nextflow, shell scripts) on HPC systems.
• Support routine monitoring of pipeline performance and help troubleshoot workflow issues, including error logging and recovery.
• Follow and help maintain best practices for version control, documentation, data integrity, and reproducibility.

• Work with investigators, clinicians, and lab members to help define analytical needs, interpret results, and provide computational support in coordination with the project lead.
• Participate in project meetings and communicate analytical updates and findings to multidisciplinary research teams.

• Assist with preparing analysis reports and supporting materials (e.g., figures and tables) as needed, under the supervision of project lead/PI.
• Help ensure analytical deliverables are clear, complete, and reproducible by adhering to established documentation and reporting standards.

Other duties as assigned.

Required:

Bachelor's degree in Biology, Biochemistry, Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, Biostatistics, Bioinformatics, Data Science, Genome Science or related field.

Preferred:
Master's degree in Biology, Biochemistry, Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, Biostatistics, Bioinformatics, Data Science, Genome Science or related field.

Required:

None

Preferred:
Machine Learning and/or Bioinformatics experience in a academic environment.

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…