Postdoctoral Research Associate in MALDI Imaging Mass Spectrometry
Los Alamos National Laboratory · Los Alamos, NM · 3 wk ago
AnalystFull-time
About the role
The Postdoctoral Research Associate will focus on advancing MALDI imaging mass spectrometry (IMS) methods and data workflows. This role involves spatially mapping biomolecules across diverse sample types and translating IMS data into actionable biological insights. The position leverages state-of-the-art high-resolution mass spectrometers and robust high-performance computing resources to conduct mission-driven research with national security applications.
Responsibilities
- Develop, optimize, and apply MALDI IMS sample-preparation and acquisition methods for targeted and discovery spatial analyses.
- Build and/or improve IMS data processing, visualization, and interpretation pipelines, including spatial statistics where appropriate.
- Collaborate with multidisciplinary teams to integrate IMS outputs with complementary measurements and biological context.
- Implement and document quality control approaches appropriate for IMS studies (reference standards, process controls, and system-performance checks).
- Communicate results through peer-reviewed publications, technical reports, and conference presentations.
Requirements
- Ph.D. in a STEM field completed within the last five years (or expected by the start date).
- Strong peer-reviewed publication record commensurate with career stage.
- Excellence in written and oral communication (e.g., manuscripts, reports, presentations).
- Deep understanding of mass spectrometry fundamentals and -omics pipeline concepts.
- Hands-on experience spanning sample preparation, instrument operation/data acquisition, and data analysis.
- Ability to obtain a DOE Q clearance (typically requires U.S. citizenship).
Qualifications
- Demonstrated experience with MALDI IMS data processing, spatial visualization, and interpretation.
- Experience developing reproducible computational workflows (e.g., scripting, version control, documented pipelines).
- Familiarity with statistics and/or machine learning methods for robust molecular panel development.
- Experience with multi-omics harmonization and integration is a plus.
- Experience designing and executing QC plans (reference/quantitative/process/system-performance controls).