Genomics Bioinformatics Researcher – Rare Diseases

Washington University in St. Louis; St. Louis (MO); On-site; USD 48,998,000 - 83,354,000; Full time

Job summary

Washington University in St. Louis seeks a Bioinformatics Research Assistant to join a collaborative team uncovering the genomic basis of rare diseases.

The role involves analyzing large whole genome and exome sequencing data, RNA sequencing, and epigenomics data to support variant discovery and prioritization. You will run computational pipelines on a local HPC cluster, manage and transfer large datasets, and help evaluate new methods while collaborating with geneticists, bioinformaticians, and

Qualifications

• Bachelor’s degree or combination of education and/or experience may substitute for minimum education.
• No specific certification/professional license is required for this position.
• No specific work experience is required for this position.
• A driver's license is not required for this position.

Responsibilities

• Run computational bioinformatics pipelines on a local high-performance computing cluster to analyze genomic datasets.
• Conduct variant analysis and curation, helping to identify genomic variants underlying rare disease.
• Maintain and manage large datasets, including data storage and data transfer of genomic data.
• Contribute to developing and refining computational workflows to improve the efficiency and accuracy of genomic data processing and analysis.
• Work closely with a multidisciplinary team of geneticists, bioinformaticians, and clinicians to communicate findings and interpret results within the context of rare disease research.
• Assist in preparing project reports, presentations, and manuscripts as needed.
• Performs other duties as assigned.

Job description

Washington University in St. Louis seeks a Bioinformatics Research Assistant to join a collaborative team uncovering the genomic basis of rare diseases.

The role involves analyzing large whole genome and exome sequencing data, RNA sequencing, and epigenomics data to support variant discovery and prioritization. You will run computational pipelines on a local HPC cluster, manage and transfer large datasets, and help evaluate new methods while collaborating with geneticists, bioinformaticians, and