Bioinformatics Engineer
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Responsibilities
- Evaluate existing bioinformatics pipelines for performance, accuracy, and maintainability, identifying opportunities for optimization and enhancement
- Develop, extend, and maintain Nextflow workflows for bulk RNA-seq, single-cell RNA-seq, DNA variant calling, methylation analysis, and emerging assay types
- Architect scalable solutions capable of processing thousands of samples efficiently on Google Cloud Platform
- Optimize data input/output operations across pipeline modules to minimize bottlenecks and reduce computational costs
- Prepare and structure analysis outputs for visualization platforms and downstream statistical or machine learning applications
- Implement best practices for workflow versioning, containerization, testing, and documentation
- Collaborate with computational biologists, data scientists, and software engineers to integrate pipelines into broader analytical ecosystems
- Stay current with advances in sequencing technologies and analytical methods, evaluating and incorporating new tools as appropriate
- Required Qualifications
- Master's degree in bioinformatics, computational biology, computer science, or a related field (or equivalent experience)
- 3+ years of hands-on experience developing and maintaining bioinformatics pipelines in a production environment
- Proficiency with Nextflow (DSL2) and familiarity with workflow management concepts
- Strong experience with RNA-seq analysis (both bulk and single-cell) and DNA sequencing workflows (variant calling, methylation)
- Working knowledge of Google Cloud Platform services (Compute Engine, Cloud Storage, Batch, Life Sciences API, or similar)
- Proficiency in Python and/or R for scripting, data manipulation, and tool development
- Experience with containerization technologies (Docker, Singularity)
- Familiarity with version control systems (Git) and CI/CD practices
- Strong understanding of genomic file formats (FASTQ, BAM, VCF, BED) and common bioinformatics tools (STAR, Salmon, BWA, GATK, Bismark, Cell Ranger, Seurat, Scanpy )
Requirements
- PhD in a relevant field
- Experience with nf -core pipelines and community standards
- Familiarity with workflow orchestration at scale (Cromwell, AWS Batch, or similar platforms)
- Experience optimizing cloud costs and resource utilization for large-scale genomics workloads
- Knowledge of data visualization tools and frameworks (e.g., R Shiny, Plotly , custom dashboards)
- Experience in pharmaceutical, biotech, or regulated research environments
- Familiarity with FAIR data principles and metadata standards
Benefits
Additional Information
(ID: 2026-2391) Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH). Axle is seeking a Bioinformatics Engineer to join our vibrant team at the National Institutes of Health (NIH) supporting the Rockville, MD. Benefits We Offer: 100% Medical, Dental & Vision Coverage for Employees Paid Time Off and Paid Holidays 401K match up to 5% Educational Benefits for Career Growth Employee Referral Bonus Flexible Spending Accounts: Healthcare (FSA) Parking Reimbursement Account (PRK) Dependent Care Assistant Program (DCAP) Transportation Reimbursement Account (TRN) Axle is seeking a skilled Bioinformatics Engineer to join our team supporting major pharmaceutical clients. In this role, you will review, assess, optimize, integrate, and extend production-grade bioinformatics workflows for high-throughput sequencing analysis. The ideal candidate combines deep expertise in genomics analysis methods with strong software engineering practices and cloud computing experience.
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