Post-Doctoral Scientist in Land Surface Modeling

The Earth System Science Interdisciplinary Center (ESSIC)/UMD is accepting applications for a Post-Doctoral Scientist.


Date posted

July 8, 2021 12:00 am

Application deadline

Aug. 31, 2021 12:00 am


The Earth System Science Interdisciplinary Center (ESSIC)/UMD


  • United States

Job description

Post-Doctoral Scientist in Land Surface Modeling

Department: UMD/ESSIC
Starting Salary: Commensurate with experience
Closing Date: Wednesday, August 31, 2022

Project Summary:

Several additions and improvements to an existing LSM are planned during this project:

  • Improve representation of biodiversity by updating the concept of plant functional types (PFTs). Instead of static PFTs, we will implement dynamic plant traits sampled from statistical distributions generated from hyperspectral remote sensing.
  • Improve representation of lateral carbon fluxes through the harvest and transport of crop and wood products.
  • Improve representation of photosynthesis and respiration in the LSM by implementing and testing different response functions.
  • Model the flow of carbon isotopes (¹²C, ¹³C and ¹⁴C) through the LSM to better distinguish processes.

The improved LSM will be run for both the historical era and for future climate projections to evaluate carbon-climate feedbacks. The improvements will be evaluated using plot-scale surface data and measurements of atmospheric CO₂ and its isotopes. The work is a collaboration between NASA Goddard Space Flight Center (GSFC), NASA Jet Propulsion Laboratory (JPL), University of Maryland, University of Colorado, and National Oceanic and Atmospheric Administration (NOAA).


Required and Desired Skills: A PhD in atmospheric or oceanic science, remote sensing, applied mathematics, physics, scientific computing, computer science, chemistry, or related technical discipline is required. Expertise in at least one compiled (such as C, Fortran, C++…) and one scripting (such as R, Python, Perl…) language is required. Experience with numerical modeling and using distributed high-performance computing systems is highly desirable. Experience with additional software tools such as Git or Mercurial for version control and expertise in geoscientific data visualization is preferred. The candidate will be expected to carry out model development, data analysis and visualization, and disseminate results through publications and conference presentations.

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