Postdoc: Spatial Omics & Biostatistics

University of Texas MD Anderson Cancer Center; Houston (TX); On-site; USD 64,000 - 76,000; Full time

Job summary

The University of Texas MD Anderson Cancer Center's Department of Biostatistics is seeking a Postdoctoral Fellow to conduct methodological research in spatial transcriptomics and computational biology. The fellow will develop novel computational methods for spatial omics data and work under Dr.

Ziyi Li's supervision. The role emphasizes scalable software development in R and Python, evaluation via simulations, and application to large cancer datasets in collaboration with researchers.

Qualifications

• Applicants should have a recent PhD in Biostatistics, Statistics, Bioinformatics, Computer Science, Computational Biology, Biomedical Informatics, or a closely related quantitative field.
• Strong programming skills in R and Python are required.
• Experience with spatial omics, single-cell data, and machine learning is highly desirable.

Responsibilities

• Develop methodological research in spatial transcriptomics and computational biology.
• Create scalable software tools and evaluate methods via simulations and benchmarking.
• Collaborate with cancer researchers to apply methods to large-scale spatial and single-cell datasets.

Skills

Programming in R and Python

Spatial omics knowledge

Machine learning / AI background

Scientific communication

Education

PhD in Biostatistics or related field

Tools

R

Python

HPC

Deep learning frameworks

Job description

The University of Texas MD Anderson Cancer Center's Department of Biostatistics is seeking a Postdoctoral Fellow to conduct methodological research in spatial transcriptomics and computational biology. The fellow will develop novel computational methods for spatial omics data and work under Dr.

Ziyi Li's supervision. The role emphasizes scalable software development in R and Python, evaluation via simulations, and application to large cancer datasets in collaboration with researchers.