Location: United States
Cap-Exempt H-1B Position — No lottery required
**Position Summary** The Biomarkers Core Laboratory seeks a bioinformatics scientist (Staff Associate II) with expertise in high-resolution mass spectrometry datasets and untargeted HRAM metabolomics data processing. This position supports the precision-medicine metabolomics and exposomics initiatives at the Irving Institute for Clinical and Translational Research, in close collaboration with the Center for Innovative Exposomics at the Mailman School of Public Health. The successful candidate will play a central role in the development, optimization, and implementation of computational workflows for large-scale, multi-omic integration of metabolomics and exposomics to advance our understanding of environmental drivers of human health and disease. **Duties** **60%:** Independently process, analyze, and interpret large-scale untargeted LC-HRMS metabolomics datasets. Execute and maintain high-performance computational pipelines for spectral processing, feature detection, annotation, statistical modeling, and data visualization. Perform QC monitoring and longitudinal dataset assessment to ensure analytical reproducibility and data integrity across projects. Apply bioinformatic tools and computational strategies to address analytical challenges in metabolomics and multi-omic data integration. **25%:** Develop, implement, and optimize automated workflows integrating R, Python, and related programming environments to support high-throughput metabolomics and exposomics data processing. Maintain and support in-house analytical platforms and associated computational infrastructure; recommend and implement incremental improvements as needed. **15%:** Prepare structured analytical reports, visualizations, and summary statistics for investigators. Contribute to manuscript preparation and collaborative scientific publications. Maintain SOPs, documentation, and data archiving practices to ensure reproducibility and regulatory compliance. **Functional Knowledge** - Applied knowledg