models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems (e.g., transportation networks, manufacturing systems, and truck routing). Assessing the relevance of the intake fraction (i.e., exposure efficiency) of major emission sources as a critical metric for infrastructure design, management, and policymaking. Investigating the residual sources of PM2.5 exposure from transportation systems following electric vehicle (EV) adoption, including exposure due to emissions from electricity generation for charging EVs, buses, trucks, rail, pavement resurfacing, tire and brake wear, and supply chain effects. Conducting life-cycle uncertainty assessments of building materials, carbon sinks (e.g., carbon dioxide removal options), and alternative low-carbon fuel sources. Candidates should demonstrate a strong theoretical background and proficiency in one or more of the following areas: infrastructure systems modeling, emissions inventory development, air quality modeling (chemical transport models and/or reduced-complexity models), exposure assessment of airborne pollutants, and life-cycle assessment. The post-doctoral associate will be expected to lead research efforts and contribute to publications in reputable academic journals. Qualifications: A PhD in Civil and Environmental Engineering or a related field High proficiency in programming languages (e.g., Python or MATLAB) A strong record of authorship in peer-reviewed academic journals Excellent interpersonal and communication skills to support effective collaboration For consideration, applicants need to submit a cover letter, curriculum vitae with full publication list, statement of research interests, a transcript, and two letters of reference, all in PDF format. If you have any questions, please email aab8693@nyu.edu . The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately, and candidates will be considered until the position is filled.
