Postdoctoral Associate: Occoquan PFAS Fingerprinting and Forensics projects

Postdoctoral Associate:
Occoquan PFAS Fingerprinting and Forensics projects

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Work type: Research Faculty
Senior management: College of Engineering
Department: Civil & Environmental Engineering
Location: Blacksburg, Virginia
Categories: Engineering, Research / Scientific

The Furst Lab at the Virginia Tech Occoquan Watershed Monitoring Laboratory (OWML) invites applications for a Postdoctoral Associate position in the area of per- and polyfluoroalkyl substances (PFAS) research. The Postdoctoral Associate will lead research on the fate and transport of PFAS with a focus on the Occoquan Watershed, which supplies drinking water to approximately 1 million people in the Northern Virginia region.

This position will support several stakeholder-driven projects, with the overall goal of developing novel analytical and modeling approaches for PFAS source fingerprinting and forensics in multi-source watersheds. The Postdoctoral Associate will contribute to project design and lead laboratory work, data analysis and modelling in collaboration with the OWML PFAS research team and water utility and government stakeholders.

The Virginia Tech Occoquan Watershed Monitoring Laboratory (OWML) is operated by the Department of Civil and Environmental Engineering (CEE). The Furst Lab at OWML conducts research on emerging contaminants, organic matter, redox and disinfection processes in One Water systems. OWML is located in Northern Virginia in the suburbs of Washington DC and houses a stakeholder-funded, state-certified water quality lab that has monitored the Occoquan Watershed – the nation’s first indirect potable reuse system – for over 50 years.

OWML is also home to seven CEE faculty and more than 30 post‐doctoral associates, graduate students, laboratory and field technicians, and office staff.

• Conduct literature reviews to identify cutting‑edge PFAS source fingerprinting and forensics techniques.
• Perform advanced laboratory analyses for PFAS detection and quantification, including but not limited to liquid chromatography‑tandem mass spectrometry (LC‑MS/MS).
• Develop and validate QA/QC criteria for analytical methods and experiments, and prepare documentation and SOPs as needed.
• Participate in meetings with utility stakeholders to present results and inform research directions.
• Coordinate with OWML field and laboratory staff to plan and execute fieldwork and laboratory work.
• Conduct data interpretation related to contaminant fate and transport in natural and engineered systems.
• Lead and contribute to manuscripts for peer‑reviewed journals and reports for sponsors.
• Assist in training and mentorship of graduate students and junior laboratory technicians.
• Ensure timely completion of project milestones and deliverables, maintain timely and professional communication with internal and external collaborators.
• Attend weekly lab meetings, support shared lab operations, and assist with proposal development.
• Receive training in project management and grant writing, and have opportunities to present findings at regional and national conferences.
• Occasional travel may be required for field work, project meetings and conferences.

• Ph.D. in Environmental Engineering, Chemical Engineering, Environmental Chemistry, or a related field. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
• Demonstrated expertise in fate and transport of emerging contaminants in natural or engineered systems.
• Extensive training and experience with PFAS analysis and LC‑MS/MS instrumentation.
• Strong scientific writing skills.
• Competency in programming and statistical analysis for advanced data interpretation.

• Record of peer‑reviewed publications and successful fellowship proposals.
• Experience mentoring students or laboratory personnel.
• Experience collaborating with governmental and industry partners.
• Familiarity with environmental policy and regulatory frameworks.
• Experience in data science, computational chemistry, and/or contaminant transport modeling.

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