Starting Salary: Commensurate with experience
Closing Date: Open until filled
We encourage applicants to apply for an open post-doctoral research position to study coupled atmospheric/oceanic/sea-ice modeling and data assimilation strategies within the NOAA Unified Forecast System (UFS). This work will be performed at the NOAA Center for Weather and Climate Prediction in College Park, MD, USA, under the guidance of scientists from the University of Maryland (UMD) and the NOAA National Center for Environmental Prediction (NCEP) Environmental Modeling Center (EMC). Scientific advancements achieved over the course of this work will directly benefit operational environmental predictions on time scales of hours to months. Given the broad range of science topics related to this project, the hired postdoc will have freedom to steer the direction of new scientific advancements related to the UFS. The general science goals of this project include the following:
- Exploring outstanding challenges associated with sea ice data assimilation, namely non-Gaussian errors and uncertainty in oceanic, atmospheric, and wave forcing.
- Developing and testing new coupled marine data assimilation methodology within the Joint Effort for Data Assimilation Integration (JEDI) framework. Potential topics include exploring new choices of control variables, new observations, and new data assimilation methodology.
- Compare findings and methodology differences between the NOAA UFS and the experimental Geophysical Fluid Dynamics Laboratory (GFDL) Seamless System for Prediction and Earth System Research (SPEAR)
The postdoc will also share findings with scientists at GFDL, EMC, UMD, and NASA who are working on related projects that focus on model and data assimilation developments for coupled Earth-system models (UFS and SPEAR), non-Gaussian data assimilation algorithm development (JEDI and DART), and the construction of new satellite observing systems that target sea ice prediction.
- A Ph.D. degree in an Earth science discipline (e.g., geoscience, atmospheric science, oceanic science), applied mathematics, physics, scientific computing / computational science, computer science, or a related fields.
- An interest in geophysical modeling and data assimilation
- Experience running numerical models on high performing computer (HPC) platforms using MPI, OpenMP, Slurm, LSF, etc.
- Experience with high-level object-oriented programming languages (e.g., Fortran, C++), at least one scripting language (e.g., Python, Shell), and at least one version control system (preferably Git).
- Well-developed skills in data processing and visualization
- An excellent record of disseminating scientific findings in peer-reviewed journals and professional meetings
- Experience operating oceanic and sea ice models (preferably MOM6 and CICE6) and interpreting solutions
- Knowledge of Arctic oceanography
- Experience working with satellite observations
- Knowledge of modern geophysical data assimilation techniques (preferably ensemble Kalman filters or ensemble-variational methods)
Logistics: This is a 1-year postdoctoral research associate appointment, with the potential to extend to 2 years. In addition to carrying out independent and collaborative research, the hired postdoc is expected to communicate major scientific findings in peer-reviewed journals, scientific meetings, and conferences.
To Apply: Interested candidates should send a CV with a list of at least 3 professional references and a cover letter explaining how your qualifications meet the posted requirements to email@example.com.
THE UNIVERSITY OF MARYLAND IS AN EQUAL OPPORTUNITY AFFIRMATIVE ACTION EMPLOYER