The U.S. Department of Agriculture (USDA), steward of agriculture for the nation, has long been concerned about the impacts of environmental variability and weather extremes. Changes in the environmental and weather patterns can lead to unprecedented changes in the Ultraviolet-B (UV-B) radiation that reaches the Earth’s surface, raising the concern of direct and indirect effects to crops, ecosystems and humans. 

The UV-B Monitoring and Research Program (UVMRP) is guided by NIFA’s mission to invest in and advance agricultural research, education, and extension to solve societal challenges and create a vision to catalyze transformative discoveries, education, and engagement to address agricultural challenges. Specifically, the UVMRP addresses NIFA’s Strategic Plan goal to advance the development and delivery of science for agricultural, forest, and range systems adapted to climate variability and to mitigate climate impacts. 

The UVMRP fulfills these mandates with three established, long-duration program areas: 

•             Monitor and examine solar radiation (with an emphasis on UV) at the Earth’s surface,

•             Study the interaction of UV radiation upon agricultural crops/production, forests, rangelands, ecosystems, and weather extremes,

•             Develop an Integrated Agricultural Impact Assessment System.

Position Summary: The post-doctoral scientist will research the variability in surface solar irradiance (especially in the UV to visible spectra) and the atmospheric factors. The position will also explore the UVMRP network measurements through a data-driven approach with the ultimate goals of improving the data quality and deriving more agriculturally/ecologically/atmospherically important products in an (semi-)automatic and reliable manner. The work will focus on the UVMRP network data but will also utilize any relevant ground or satellite data as a supplement. This position will publish scientific findings in refereed journals, and make oral presentation at scientific conferences. This long-term program has been running for over 28 years. Funding of the position is dependent upon continued federal support that is renewed on an annual basis.  To apply and view a complete position description, please visit: https://jobs.colostate.edu/postings/99243.

Required Job Qualifications:

•             Earned Ph.D. degree in atmospheric science or geosciences, or a related discipline.

•             Expertise in the transfer of solar radiation in the atmosphere and/or the remote sensing of atmospheric parameters influencing the amount of solar radiation reaching the Earth’s surface is expected, plus a strong background in computer programming.

•             The successful candidate must be legally authorized to work in the United States by the proposed start date; NREL will not sponsor a visa for this position.

Preferred Job Qualifications:

Demonstrated experience and skills with:

•             Solar radiation transfer in the Earth’s atmosphere (especially in the UV to NIR range);

•             Radiative transfer models (e.g., TUV, MODTRAN);

•             Ground-based radiometers/spectrometers;

•             Python and its numerical libraries (e.g., tensorflow, numpy, scipy, pandas, sklearn, matplotlib) and machine learning development platforms (e.g., Kubeflow, MLflow, TFX);

•             Entire life cycle of a machine learning (ML) project, including translation of a scientific question into an ML case, data preparation, development of a portable, reliable, and scalable ML model, distributed training, and deployment.

Reflecting departmental and institutional values, candidates are expected to have the ability to advance the Department’s commitment to diversity and inclusion.