Bioinformatics Scientist — HIV Genomics & Data Pipelines

Axle; Bethesda (MD); On-site; USD 105,000 - 130,000; Full time

Benefits offered by this job

PTO & Holidays

401K match 5%

Educational benefits

Employee referral bonus

Healthcare FSA

Parking reimbursement

Dependent care program

Transportation reimbursement

Job summary

Axle in Bethesda is seeking a Bioinformatics Scientist to support HIV-focused research within NIAID's DIR/IDSS. You will analyze genomic and clinical data, develop scalable pipelines, and contribute to publications and data sharing with investigators.

The role emphasizes producing robust computational tools, validating analyses, and collaborating with laboratory and clinical teams to accelerate discoveries in translational bioinformatics.

Qualifications

• Bachelor's degree in a related field required; advanced degrees preferred.
• Minimum of 4 years in bioinformatics with 2+ years building production pipelines.
• Expert-level proficiency in two of: Python, R, C/C++, sh/bash.
• Experience with containerization and HPC environments.

Responsibilities

• Provide scientific consultation and design experiments for high-throughput data analysis.
• Support bioinformatics pipelines and data analysis across genomic and clinical datasets.
• Develop and maintain scalable production pipelines and reproducible workflows.
• Provide programming support and troubleshooting for RTB and collaborating institutes.
• Collaborate with staff on experimental design and publication efforts.
• Contribute to and co-author scientific publications in peer-reviewed journals.
• Develop scalable resources for NIAID scientists and investigators.

Skills

Python

R

C/C++

Shell scripting

Bioinformatics

HPC

Education

Bachelor's degree in related field

Master’s degree preferred

Tools

Docker

Singularity/Apptainer

Snakemake

Nextflow

CWL/WDL

Job description

Axle in Bethesda is seeking a Bioinformatics Scientist to support HIV-focused research within NIAID's DIR/IDSS. You will analyze genomic and clinical data, develop scalable pipelines, and contribute to publications and data sharing with investigators.

The role emphasizes producing robust computational tools, validating analyses, and collaborating with laboratory and clinical teams to accelerate discoveries in translational bioinformatics.