New Position Opening: PFAS and Data Science Postdoctoral Research Associate

SSEHRI’s PFAS Project Lab is seeking candidates for a new position opening for a Postdoctoral Research Associate in PFAS Research and Data Science. See below for details.

Position Description

Northeastern University’s Social Science Environmental Health Research Institute (SSEHRI) seeks a one-year postdoctoral research associate to work in the PFAS Project Lab (, led by Phil Brown (Northeastern) and Alissa Cordner (Whitman College). This position will also support an environmental health/data science training program titled, “Stackable trainings in the FAIRification and AI/ML readiness of data with applications to environmental health and justice.” Official job posting may take another week, so this position is officially “pending approval.”

1) PFAS Project Lab Responsibilities The PFAS Project Lab is made up of three faculty members, one research scientist, four graduate students, and five undergraduates, and has strong connections through grants and projects with collaborating organizations, such as Silent Spring Institute, Environmental Working Group, Green Science Policy Institute, and many PFAS-affected community groups. The postdoc will work on an NIEHS-funded project, “Health Assessment, Public Education, and Capacity-building in Communities Impacted by PFAS-contaminated Drinking Water,” led by Dr. Laurel Schaider (Silent Spring Institute), Phil Brown (Northeastern), and Courtney Carignan (Michigan State University). Tasks include: recruiting participants for a children’s immunotoxicity study; reporting back data to participants; providing community resources such as a PFAS contamination map and medical guidance documents; and interviewing participants, community advisory board members, and local residents and officials about contamination experiences. The postdoc will also work on NSF-funded projects titled, “The New Chemical Class Activism: Mobilization Around Per- and Polyfluoralkyl Substances” and, “Multi-scalar, Multi-stakeholder Environmental Governance: The Case of PFAS,” with tasks including interviewing, participant observation, and database creation and management. More information on the PFAS Project lab can be found at

2) Data Science Supplement Responsibilities The postdoc will also work on a data science training project, which is funded by a Supplement to Phil Brown’s NIEHS T32 Training Program “Transdisciplinary Training at the Intersection of Environmental Health and Social Science,” with the Supplement work being led by Professors David Kaeli, Justin Manjourides, and Jennifer Dy. The next (and current) generation of biomedical researchers must be cognizant of FAIR principles to be prepared to make their data accessible by machines in order to fully leverage the continued growth around methodological developments to properly analyze large amounts of data across multiple studies/systems/countries. In addition to a methodologic toolkit, educating the biomedical analyst workforce must include training to build their ability to locate and store data for future analyses in an automated manner. The Supplement provides a suite of stackable modules to provide a rich foundation to the existing robust educational offerings around the applications of AI/ML to biomedical data that many trainees already receive. The Supplement stems from the Data Management Core of Northeastern’s NIEHS PROTECT Superfund Research Program (directed by Drs. Kaeli and Manjourides) and from the multinational Observational Health Data Sciences and Informatics (OHDSI) community – a global, multidisciplinary open source and open science community of more than 300 organizations aimed at improving patient outcomes through large scale analytics, which is housed at the Roux Institute (a collaboration of Northeastern University and the University of Maine). The postdoc will be involved in various aspects of the training Supplement, and will be in charge of a module titled, “Artificial intelligence and machine learning fairness and bias with applications to environmental justice.”

Overall Research Setting and Opportunities The postdoc will attend bi-weekly SSEHRI meetings and bi-weekly meetings of the PFAS Project Lab, and will participate in meetings of the Training Program, “Transdisciplinary Training at the Intersection of Environmental Health and Social Science.” They will benefit from a thriving space for collaborations between life sciences and social sciences that train scholars for interdisciplinary collaborations that improve the study and remediation of environmental health issues. The postdoctoral research associate will have a regular mentor, opportunities for collaboration on existing research, involvement with other postdocs, multiple venues for presenting work in progress, the option to audit courses, ample opportunities to participate in grant and article writing, and opportunities for guest lecturing.

Northeastern University has a strong environmental health presence, including a Superfund Research Program, a Children’s Environmental Health Center, and ECHO Center (Environmental Influences on Child Health Outcomes), R01 and R21 research grants, an NIEHS T32 Training Program, an NIEHS R-25 undergraduate Training Program, and several major grants with Silent Spring Institute. The salary is $50,000 and there is a health benefits package.

To Apply

Candidates should submit application materials through the Northeastern HR website via the position posting linked here!

Three letters of reference, including one from the dissertation advisor, should be sent to The ideal start date of this position is September 2021, but it is possible to start slightly later.  Review of applications will begin immediately and the search will remain open until the position is closed or filled. For additional information write Phil Brown at:


We seek an environmental health scientist or social scientist, PhD in hand, with training and research experience in environmental health and community engagement, and preferably knowledge of PFAS science and/or policy. The ideal candidate will have experience in one or more areas of data science as well as qualitative research experience.

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