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Postdoctoral Research Fellow in Remote Sensing and Numerical Weather Modeling

Remote / Online - Candidates ideally in
Louisville, Jefferson County, Kentucky, 40201, USA
Listing for: University of Louisville
Remote/Work from Home position
Listed on 2026-10-18
Job specializations:
  • Research/Development
    Research Scientist, Data Scientist, Postdoctoral Research Fellow
Salary/Wage Range or Industry Benchmark: 52000 - 68000 USD Yearly USD 52000.00 68000.00 YEAR
Job Description & How to Apply Below

We are seeking a highly motivated Postdoctoral Researcher to join an interdisciplinary team in the Department of Geographic and Environmental Sciences at the University of Louisville working on a NASA-funded project, "Advancing land cover/land use characteristics in short-range numerical weather prediction systems for urban areas," (#80

NSSC
25K7495). The project addresses NASA Biosphere Land-Cover/Land-Use Change priorities, including the Land Use for Digital Twins (LU4DT) sub-element, by improving the representation of urban land cover and land-surface properties in short-range numerical weather prediction and Land-Earth System Digital Twin applications. Using the greater Louisville, Kentucky area as a test bed, the project integrates high-resolution, multi-sensor Earth observation data with large eddy simulations (LES), in situ meteorological observations, and scenario-based urban heat island (UHI) mitigation analyses.

The postdoctoral researcher is budgeted for 18 months beginning in Project Year 2, when the project is expected to place strong emphasis on data analysis, model integration, scenario generation, publication preparation, and other research deliverables.

Position Description and Responsibilities

The postdoctoral researcher will work across the project's four linked objectives, with substantial effort devoted to integrating remote sensing data with Weather Research and Forecasting (WRF)-like models. This includes generating simulation-ready land-surface parameters, parameterizing and running models on high performance computing (HPC) clusters, validating model output, and producing research and dissemination products. More details on the project website, found here: (Use the "Apply for this Job" box below).-prediction

Research

Environment

The successful candidate will join a collaborative University of Louisville team spanning remote sensing, geospatial science, atmospheric dynamics, numerical weather prediction, and meteorological observations. This position reports to Dr. Andrea Gaughan, PI and Professor in the Department of Geographic and Environmental Sciences but the successful applicant should anticipate close collaboration with other co-PIs, the University of Louisville Center for GIS and local governmental and community partners.

The position offers opportunities to contribute directly to NASA LCLUC/LU4DT science, high-resolution urban modeling, open research products, peer-reviewed publications, and applied urban heat decision support.

Essential Duties and Responsibilities Numerical Weather Modeling & Remote Sensing Integration
  • Ingest high-resolution, remotely sensed gridded land-surface products into atmospheric modeling systems, specifically focusing on the Weather Research and Forecasting (WRF) model and Noah-MP LSM integration.
  • Modify, configure, and execute numerical weather prediction workflows on HPC platforms, including LES experiments that evaluate model sensitivity to dynamic atmospheric and land-surface parameters.
  • Process and aggregate multi-source Earth observation data (optical, radar/SAR, LiDAR, and infrastructure datasets) into spatially dynamic, simulation-ready parameters (e.g., albedo, canopy properties, surface roughness) for model input.
  • Post-process, analyze, and visualize numerical model outputs to evaluate model performance against nested WRF simulations and field observations.
  • Collaborate with the project team on managing, processing, and quality-controlling observational data from the local meteorological micronet.
  • Quantitative assessment of model accuracy by comparing simulation output against in situ micronet data.
  • Execute scenario-based WRF simulations to assess how urban heat…
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