Senior Metabolomics Bioinformatics Scientist

Georgetown University; United States; On-site; USD 48,000 - 88,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Retirement Savings

Tuition Assistance

Work-Life Balance Benefits

Job summary

Georgetown University’s Metabolomics Shared Resource (MSR) seeks a Bioinformatics Scientist to design experiments and perform QC, data integrity checks, batch normalization, and pre/post-processing of LC-MS data across metabolomics studies.

The role emphasizes collaboration with wet-lab scientists to integrate multi-omics data and develop robust analytical pipelines for high-dimensional datasets, enabling data uploads to centralized repositories.

Qualifications

• MS in bioinformatics and/or biostatistics or computational biology; PhD preferred.
• Experience analyzing and integrating multi-dimensional omics data.
• Experience with R/Bioconductor.
• Strong written and oral communication; ability to work independently and in team.

Responsibilities

• Process raw LC-MS and GC-MS data for statistical analysis-ready formats.
• Develop and streamline bioinformatics pipelines for pre/post-processing.
• Perform advanced analyses on high-dimensional omics datasets including metabolomics.
• Communicate results to clients and support experimental design.
• Develop an integrated analytical pipeline around instrument software and public resources.
• Stay updated on developments to improve the platform.

Skills

Multi-omics data integration

R programming

Data visualization

Communication skills

Education

MS in bioinformatics/biostatistics/computational biology

PhD in a related field preferred

Tools

R/Bioconductor

LC-MS data processing tools

Job description

Georgetown University’s Metabolomics Shared Resource (MSR) seeks a Bioinformatics Scientist to design experiments and perform QC, data integrity checks, batch normalization, and pre/post-processing of LC-MS data across metabolomics studies.

The role emphasizes collaboration with wet-lab scientists to integrate multi-omics data and develop robust analytical pipelines for high-dimensional datasets, enabling data uploads to centralized repositories.