Job Board
- Postdoctoral Researcher
Job summary
Dr. McKenzie Skiles and Dr. Carlos Oroza at the University of Utah are seeking a postdoctoral researcher for an upcoming NOAA-funded research project, under the CIROH cooperative institute (https://ci.noaa.gov/Locations/CIROH). The project will develop new high-resolution data products and model enhancements for the next generation National Water Model (NextGen) to advance short- (<18hrs) to long-term (2-3 months) streamflow forecasts in snow-dominated regions. The initial focus will be on NextGen simulated snowpack in the headwater catchments of the Upper Colorado River Basin. The objective is to improve simulated snow mass and energy balance using numerical weather prediction models, ground and satellite remote sensing retrievals, and data assimilation. The postdoctoral researcher will contribute to model development and analyzing model outputs and to disseminating results through conference presentation and peer-reviewed publications.
The successful candidate must have relevant skills in terms of numerical modeling, remote sensing, and data analysis that will allow them to meaningfully contribute to product and model development and analysis of model outputs. It is expected the researcher will work collaboratively with the project team, but will also be encouraged to develop their own related research questions and objectives.
Skills and Responsibilities
Qualifications:
PhD in related field (e.g. earth/environmental science, geology/geography, civil and environmental engineering)
Skills:
- High-level programming experience (Python, Matlab etc.)
- Version control (e.g. Github)
- Distributed numerical modeling (NWM experience a plus)
- Remote sensing familiarity (LIDAR, multispectral satellite retrievals with experience in assimilating such datasets a plus)
Example responsibilities include:
- Producing precipitation datasets from HRRR, including downscaling from native resolution (3 km) to NextGen resolution
- Producing albedo parameters from historical MODIS record
- Assimilating a machine-learning-derived SWE product
- NWM implementation of forcing updates and output adjustment (i.e. model enhancements)
Start date is on or after August 1st, 2022 and position length is three years. Start date and term are contingent upon funding availability.
Applications should include a CV, cover letter that includes a statement of interest and description of relevant research background, and three contacts from which letters of recommendation can be requested. Applications, or any questions and inquiries, should be sent to both Dr. McKenzie Skiles (This email address is being protected from spambots. You need JavaScript enabled to view it.) and Dr. Carlos Oroza (This email address is being protected from spambots. You need JavaScript enabled to view it.).