The High Meadows Environmental Institute (HMEI; https://environment.princeton.edu) invites applications for multiple postdoctoral research associates to join Dr. Gabriele Villarini's research group (www.gabrielevillarini.com). These positions will contribute to the development and application of an integrated hydrologic-hydraulic modeling framework, with the goal of improving the representation, coupling, and scalability of physical, ecological, disturbance, and human processes across spatial and temporal scales.

The research will involve multi-decadal, continental-scale hydrologic and hydraulic simulations, flood-inundation mapping, and the coupling of these modeling capabilities with vegetation dynamics, fire processes, and socio-economic impact assessments under current and future conditions.

Positions are for one year with the possibility of renewal pending satisfactory performance and continued funding.

Applicants should apply under one primary focus area from the list below, although cross-cutting expertise and interest in collaborative, integrated model development are strongly encouraged.

Primary Focus Areas include:

1. Computational Hydrology: Leading large-scale hydrologic modeling efforts using the GPU-based Tiger-HLM, including continental-scale simulations, high-performance computing workflows, and analysis of long-term and large-ensemble forcing datasets. The position will involve refining model formulations, implementing methodological improvements, and running and evaluating simulations to support flood hazard and risk analyses across large river basins.

2. Hydraulic and Flood-Inundation Modeling: Development and application of physically based flood-inundation modeling to translate hydrologic model outputs into high-resolution flood hazard information (riverine, coastal, and pluvial). The position will focus on implementing, refining, and efficiently applying two-dimensional hydrodynamic modeling using TRITON, including large-domain simulations, targeted high-impact scenarios, and close integration with hydrologic simulations and terrain representations.

3. Terrain and DEM Characterization for Hydrologic and Hydraulic Modeling: Development, assessment, and refinement of digital elevation model (DEM) products to improve hydrologic and hydraulic model performance across large spatial domains. The position will focus on DEM conditioning, channel and floodplain representation, and integration of multi-source elevation data to support scalable hydrologic simulations and physically based two-dimensional hydraulic modeling.

4. Vegetation and Ecohydrologic Modeling: Coupling vegetation dynamics with hydrologic variability to examine how soil properties, rainfall amount, seasonality, and interannual variability influence plant productivity, allocation, phenology, and functional traits in dryland and savanna ecosystems. The position will involve integrating or extending vegetation components within the Tiger-HLM hydrologic modeling framework, in close coordination with hydrologic model development.

5. Fire Modeling and Fireâ“Hydrology Interactions: Modeling wildfire occurrence, behavior, and impacts as stochastic disturbance processes and their interaction with hydrologic variability and vegetation dynamics. The position will focus on representing fire effects on vegetation structure, productivity, and trait expression within an integrated hydrologic-hydraulic-vegetation modeling framework, with particular emphasis on dryland and savanna systems and postâ‘fire hydrologic response.

6. Socio-Economic Impacts and Human Systems: Quantitative integration of hydrologic, hydraulic, and related model outputs with socio-economic, demographic, infrastructure, and land-use data to assess impacts, vulnerability, risk, and equity-relevant outcomes associated with water-related hazards. The position will focus on developing and applying reproducible, data-driven frameworks that link physical hazard modeling with human exposure and vulnerability across large spatial domains.

Required Qualifications: Ph.D. in a relevant science, engineering, or related field is required. Candidates from fields including hydrology, hydraulics, environmental engineering, earth system science, ecology, fire science, geography, applied mathematics, computer science, economics, or related disciplines are particularly encouraged to apply.

Experience in numerical, process-based, or data-driven modeling, and in processing and analyzing large datasets and model outputs, is required. Experience with hydrologic and/or hydraulic models is required for some focus areas (Focus Areas 1 and 2), and highly desirable for all. Candidates with experience in model development, model coupling, or extension of existing modeling frameworks (e.g., hydrologic, hydraulic, vegetation, fire, or impact models) are particularly encouraged to apply.

Expertise in computer programming and experience with high-performance computing environments are required.

Desired Qualifications: Knowledge of compiled languages (e.g., C/C++) and/or parallel computing paradigms is desirable. Successful candidates will demonstrate the ability to work across disciplinary boundaries and to contribute to shared, open, and reproducible modeling frameworks.

This position is subject to the University's background check policy. The work location for this position is in-person on campus at Princeton University.

Applicants must submit a cover letter, curriculum vitae, a brief statement of research interest, and names and contact information for three references. All materials must be submitted online.

This position is not eligible for sponsorship of an H-1B visa requiring consular processing; other visa sponsorships (including H-1B visas not requiring consular processing) may be available, as appropriate.