[ES_JOBS_NET] Postdoc positions in modeling aerosols and aerosol-cloud interaction at global convection-permitting scales

[Ma, Po-Lun]

The Atmospheric Sciences and Global Change Division at Pacific Northwest National Laboratory (PNNL) is seeking highly motivated postdoctoral research associates to work on modeling aerosols and aerosol-cloud interactions at global convection-permitting scales for the U.S. Department of Energy’s (DOE’s) Energy Exascale Earth System Model (E3SM; http://e3sm.org/ ), as part of the “Enabling Aerosol-cloud interactions at GLobal convection-permitting scalES (EAGLES)” project. Targeted at DOE’s leadership computing facilities (e.g., GPU-based systems), the project seeks to develop robust and computational efficient parameterizations to represent aerosols and aerosol-cloud interactions. The work will be carried out in close collaboration with scientists at PNNL, Sandia National Laboratories, and various universities.


  *   Representing aerosols and aerosol-cloud interactions (Job ID: 309932): The incumbent will work on the development and evaluation of new data-driven process representations for aerosols and aerosol-cloud interactions using novel machine learning techniques based on LES and observations. The selected candidate will implement new parameterizations in E3SM, evaluate the new model (using regional refined mesh), and assess the impacts on weather and climate. The candidate should have demonstrated experience in atmospheric model development, evaluation, and analysis. Experience in novel data-model integration techniques such as data assimilation and machine learning will be considered favorable during the evaluation. To apply, visit https://careers.pnnl.gov/JobOpeningID=309932


  *   Cloud microphysics parameterization (Job ID: 309931): The incumbent will work on improving the representation of cloud microphysical processes and aerosol-cloud-precipitation interactions. Development will be guided by observations and spectral bin microphysics (SBM) model simulations from the high-resolution Weather Research and Forecasting (WRF). The candidate should have demonstrated expertise in modeling cloud microphysical processes and working knowledge of bulk and/or explicit cloud parameterizations used in atmospheric models. To apply, visit https://careers.pnnl.gov/JobOpeningID=309931


  *   Computational aspects of modeling aerosols and clouds (Job ID: 309961): The incumbent will work at the exciting interface between atmospheric physics and computational sciences. Possible assignments will include assessing and improving the accuracy and efficiency of numerical methods for individual parameterizations and their coupling, speeding up code execution using mixed-precision calculations, and developing testing strategies and software to ensure code trustworthiness. The candidate should have demonstrated expertise in numerical model development on high-performance computing platforms. To apply, visit https://careers.pnnl.gov/JobOpeningID=309961


  *   Observational analysis and model evaluation of aerosols and aerosol-cloud interactions (Job ID: 309889): The incumbent will develop methodologies of evaluating E3SM at convection-permitting scales using a wide range of routine and field campaign measurements of meteorology, radiation, clouds, and aerosol properties. The candidate should have demonstrated expertise in performing analyses of measurements, understanding measurement uncertainties, and appropriately comparing observations and model output. To apply, visit https://careers.pnnl.gov/JobOpeningID=309889

Please visit the webpages above for more information (e.g., requirements and preferred qualifications) about the positions. In general, the candidate needs to understand various processes that control the cloud or aerosol lifecycle. Proficiency with FORTRAN and coding experience with atmospheric models are required. The ability to modify, compile, and run global or regional atmospheric general circulation models (e.g., E3SM, CESM, WRF, etc.) is desirable. Experience with C++ and running on GPU-based supercomputers is a plus. The candidate is expected to be a strong team player with the willingness and ability to work independently.

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