Jobs:Job-00403
Apply before: 30 July 2021
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Posting:
Position: (postdoctoral) research position
Apply before: 30 July 2021
Apply online:
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Put your land surface modeling talents to good use by joining the Earth and Environmental Science Division at Los Alamos National Laboratory (LANL). LANL is a multi-disciplinary research institution engaged in science on behalf of national security. You will work with a multi-disciplinary team of observational and computational earth scientists, hydrologists, ecologists and computer scientists in an effort to understand the rate and patterns of landscape change in the Arctic and its impact and feedbacks on carbon and nutrient fluxes.
Your research will include Arctic land-surface modeling using the U.S. Department of Energy’s Energy Exascale Earth System (E3SM; https://e3sm.org/ ) model and may include:
- Modeling representations of permafrost hydrology in numerical, land surface, or watershed models
- Use of direct and remotely sensed observations, including drone-based acquisitions, for Arctic permafrost trend analysis and model validation.
- Trips to Alaska to support the collection of field observations.
While the large-scale research goals for the project have been established, there is significant flexibility in the way these goals may be achieved. A self-motivated, creative postdoc will find this environment conducive to intellectual and professional growth. A comprehensive knowledge of the novel components of the research activities will not be necessary as on-the-job training will support the candidate’s success through a collaborative team atmosphere.
We seek applications from diverse candidates with expertise in any of the following research areas: land surface modeling and analysis, numerical analysis, and frozen ground modeling. Candidates with experience working in and/or analyzing Arctic and permafrost-affected landscapes and thermally-influenced hydrological processes are particularly encouraged to apply. We invite applications from individuals with interests in developing and implementing models for diverse computational architectures (desktop to HPC and cloud).
