The Functional and Systems Biology group within the Environmental Molecular Sciences Division at Pacific Northwest National Laboratory (PNNL) is seeking a postdoctoral research associate to support the development, operation, and application of Fourier transform mass spectrometry (FTMS) platforms, including Orbitrap and FTICR-based systems. This work is conducted within the Environmental Molecular Sciences Laboratory (EMSL), a U.S. Department of Energy Office of Science User Facility, and will involve close interaction with internal researchers and external users. The successful candidate will work as part of a multidisciplinary team to design and execute experiments leveraging high-resolution mass spectrometry for biological and environmental systems, including plant, microbial, soil, aqueous, and aerosol samples. Research efforts will contribute to applications in biotechnology, the bioeconomy, and the characterization of systems relevant to critical materials and mineral cycling, while maintaining a primary focus on advancing FTMS capabilities and methodologies. Responsibilities include operation of commercial and custom-modified instrumentation, implementation of new experimental methods, and systematic evaluation of instrument performance. The candidate will contribute to ongoing research and development efforts by assisting in instrument troubleshooting, maintenance, and incremental hardware and method improvements. This role will involve working with experimental systems that may not have established workflows, requiring the ability to diagnose issues, adapt approaches, and document procedures for broader use. Additional responsibilities include developing and applying programmatic data analysis workflows (e.g., Python-based approaches) to evaluate experimental results, quantify performance metrics, and support reproducible analysis of complex datasets. The candidate will be encouraged to leverage emerging approaches in automation, machine learning, and AI-assisted analysis where appropriate to improve experimental throughput, data interpretation, and reproducibility. The postdoctoral researcher will collaborate with interdisciplinary teams and EMSL users, contribute to scientific publications and reports, and ensure compliance with laboratory safety and operational standards. This role provides an opportunity to engage in cutting-edge user-driven science while developing expertise in advanced mass spectrometry instrumentation and data-driven experimental workflows. Qualifications. Minimum Qualifications:Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university. Preferred Qualifications:The ideal candidate will have a PhD. in chemistry, analytical chemistry, physics, engineering, or a related field, with experience in mass spectrometry or advanced analytical instrumentation. Familiarity with high-resolution mass spectrometry platforms (e.g., Orbitrap, FTICR, or Q-TOF) and tandem MS experiments is desirable. Candidates should demonstrate experience designing and executing experiments involving complex chemical or biological systems, such as metabolomics, proteomics, environmental samples, or complex mixtures. Experience operating laboratory instrumentation and performing basic troubleshooting and maintenance is expected. Experience with programming or scripting (e.g., Python) for data analysis, visualization, or workflow automation is highly desirable. Candidates should show an interest in developing reproducible and scalable data analysis approaches rather than relying on manual or spreadsheet-based workflows. An interest in instrument development, method development, or performance characterization is advantageous. Exposure to emerging approaches in automation, machine learning, or AI-assisted data analysis is beneficial but not required. The successful candidate should be comfortable working in multidisciplinary teams and engaging with EMSL users in a collaborative research environment. Strong written and oral communication skills are required, along with evidence of scientific productivity (e.g., publications or presentations).