Bioinformatics Scientist - Genomics & Spatial Transcriptomics

The University of Texas Medical Branch; Galveston (TX); On-site; USD 95,000 - 140,000; Full time

Job summary

The University of Texas Medical Branch in Galveston invites applications for a research academic position focused on bioinformatics and genomics. The successful candidate will design and implement pipelines for large-scale sequencing data and collaborate with wet-lab scientists to advance biomedical research.

Required qualifications include a PhD or equivalent in a related field and at least one year of related experience; expertise in transcriptomics, spatial data analysis, and HPC is highly

Qualifications

• PhD, MD, DO, or DVM in a related field and one year of related experience.
• Strong background in bioinformatics and genomics preferred.
• Experience with transcriptomics and spatial data analysis is desired.

Responsibilities

• Design and implement bioinformatics pipelines for genomics and transcriptomics data.
• Collaborate with wet-lab researchers to plan experiments and interpret results.
• Develop, maintain, and document bioinformatics tools and software.
• Integrate, visualize, and analyze genomic data from multiple sources.
• Process sequencing data and deliver results to researchers.
• Publish scientific findings and reports.

Skills

Bioinformatics

Transcriptomics

Spatial transcriptomics

Python

R

Perl

Cloud computing

Team collaboration

Independent work

Education

PhD in related field

MD/DO/DVM in related field

Tools

Xenium platform

High-performance computing

Job description

The University of Texas Medical Branch in Galveston invites applications for a research academic position focused on bioinformatics and genomics. The successful candidate will design and implement pipelines for large-scale sequencing data and collaborate with wet-lab scientists to advance biomedical research.

Required qualifications include a PhD or equivalent in a related field and at least one year of related experience; expertise in transcriptomics, spatial data analysis, and HPC is highly