Postdoc: Computational Genomics & Bioinformatics

Texas A&M University System; Bryan (TX); On-site; USD 60,000 - 90,000; Full time

Job summary

Texas A&M University Health Science Center invites applications for a Postdoctoral Research Associate in Computational Biology at the Bryan, Texas location. The role involves conducting computational analyses, data interpretation, and contributing to publications, with opportunities to supervise students and assist in grant writing.

The candidate should have a PhD in a relevant field and strong experience with RNA-seq, ATAC-seq, ChIP-seq datasets in UNIX/Linux environments, and proficient coding

Qualifications

• PhD required in computational biology-related field.
• Strong programming skills in Python, R and/or Perl.
• Experience analyzing genomics, transcriptomics, and epigenomics data (RNA-seq, ATAC-seq, ChIP-seq).
• Experience with high-performance computing environments.
• Data-management and data-processing pipelines development experience.
• Proficiency in R, Python, MATLAB; familiarity with software development practices.

Responsibilities

• Conduct hypothesis-driven computational research with appropriate controls.
• Analyze large-scale sequencing data and build quantitative models.
• Interpret results and discuss implications for publications.
• Maintain and update software on the TAMU cluster; contribute to codebase and Git repositories.
• Supervise undergraduate/graduate students and collaborate with other labs.
• Present findings at group meetings and conferences; assist in grant-writing as needed.

Skills

Python

R

Perl

Matlab

RNA-seq

ATAC-seq

ChIP-seq

HPC

Data pipelines

Statistics

Machine learning

Version control

Team collaboration

Education

PhD in Computational Biology / Bioinformatics / Computer Science

Tools

UNIX/Linux

Git

Job description

Texas A&M University Health Science Center invites applications for a Postdoctoral Research Associate in Computational Biology at the Bryan, Texas location. The role involves conducting computational analyses, data interpretation, and contributing to publications, with opportunities to supervise students and assist in grant writing.

The candidate should have a PhD in a relevant field and strong experience with RNA-seq, ATAC-seq, ChIP-seq datasets in UNIX/Linux environments, and proficient coding