Senior Integrated Wet-Lab & Computational Scientist

University of Texas Southwestern Medical Center; Dallas (TX); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

PPO medical plan

100% preventive healthcare coverage

Paid Time Off

Retirement Programs

Paid Parental Leave

Wellness programs

Tuition Reimbursement

PSLF Qualified Employer

Learn more about benefits

Job summary

UT Southwestern Medical Center in Dallas seeks a Computational Biologist II to bridge wet-lab experiments with computational analysis. You will lead analyses of scRNA-seq, spatial transcriptomics, and multi-omics data, develop reproducible pipelines in R and Python, and contribute to publications.

Collaboration with investigators and mentors is a core part of the role, with opportunities for growth in a dynamic lab focused on injury, regeneration, and cancer biology.

Qualifications

• PhD or Master/Bachelor with bioinformatics training.
• 2 years post-Master or 4 years post-Bachelor experience in bioinformatics/computational biology.

Responsibilities

• Design integrated experimental and computational strategies with the PI and collaborators.
• Analyze scRNA-seq, snRNA-seq, bulk RNA-seq, spatial transcriptomics, and other omics data.
• Develop reproducible pipelines in R and Python using version control and containerization.
• Mentor trainees and staff in computational biology and statistics.
• Publish findings and present in meetings and manuscripts.

Skills

R

Python

Bioinformatics

Single-cell analysis

Spatial transcriptomics

Machine learning

Data visualization

Education

PhD in Computer Science or related field

MS in Computer Science or related field

BS in Computer Science or related field

Tools

Seurat

Scanpy

Bioconductor

Signac

ArchR

Cell Ranger

Job description

UT Southwestern Medical Center in Dallas seeks a Computational Biologist II to bridge wet-lab experiments with computational analysis. You will lead analyses of scRNA-seq, spatial transcriptomics, and multi-omics data, develop reproducible pipelines in R and Python, and contribute to publications.

Collaboration with investigators and mentors is a core part of the role, with opportunities for growth in a dynamic lab focused on injury, regeneration, and cancer biology.