Graduate Research Assistant: Computational Biology

Penn State University; University Park (TX); On-site; USD 30,000 - 40,000; Part time

Job summary

Penn State University invites applications for Graduate Research Assistant roles with the NCEMS at University Park. The positions are half-time to full-time depending on semester demand, with 20 hours per week on-site in the Benkovic Building and mentorship by NCEMS staff.

Ideal candidates are PhD students in bioinformatics, genomics, data science, statistics, or biomedical informatics, with strong Python/R skills and experience in reproducible workflows for high-throughput data.

Qualifications

• Experience with Python or R.
• Experience with machine learning applications.
• Experience with multi-modal integration of data types.
• Workflow languages such as Snakemake or Nextflow.
• Proficiency in Python and R.
• Experience with transcriptomics and gene regulatory data.

Responsibilities

• Support NCEMS Working Groups and contribute to community-scale synthesis research.
• Process and analyze molecular and cellular datasets, including transcriptomics and gene regulatory data (ChIP-seq, ATAC-seq, Hi-C).
• Develop, run, and maintain reproducible computational pipelines and workflows.
• Analyze multi-omics datasets for synthesis research.
• Produce well-documented code, notebooks, and workflows.
• Provide weekly progress updates to mentoring staff.
• Prepare interim and final reports or presentations.
• Attend regular meetings with staff and Working Group members.

Skills

Python

R

Machine learning

Data analysis

Education

PhD student

Tools

Snakemake

Nextflow

Git

Job description

Penn State University invites applications for Graduate Research Assistant roles with the NCEMS at University Park. The positions are half-time to full-time depending on semester demand, with 20 hours per week on-site in the Benkovic Building and mentorship by NCEMS staff.

Ideal candidates are PhD students in bioinformatics, genomics, data science, statistics, or biomedical informatics, with strong Python/R skills and experience in reproducible workflows for high-throughput data.