Full Time Regular Position

Location: Boulder, Colorado

Hybrid work schedule:  Require 2-3 days a week on-site

Application Deadline: October 30, 2024.

This position works closely with the Mauna Loa Solar Observatory (MLSO) science team to validate existing scientific image processing pipelines, work with the MLSO team on new data pipelines, assess data quality, develop and test new algorithms to improve MLSO data, and provide data tools for use by the community.

The Mauna Loa Solar Observatory acquires unique low and middle solar corona data from two coronagraphs: the Upgraded Coronal Multi-Channel Polarimeter (UCoMP) and the COSMO K-Coronagraph (K-Cor). These instruments provide observations of coronal plasma motions, thermal conditions, and plasma density and diagnostics of the coronal magnetic field. High-time cadence observations are also acquired to track the formation and dynamics of explosive events known as Coronal Mass Ejections (CMEs) that can drive radiation and geomagnetic storms on Earth.

 A brief summary of what one would expect to be generally responsible for in this role:

·         Work with the instrument scientists and MLSO team to develop science data products from new instrumentation.

·         Help develop higher-level MLSO data products and community software tools for all MLSO instruments. As necessary, support the data pipeline manager with reprocessing MLSO data.

·         Improve existing calibration algorithms and verify the quality of the final science data products to the community.

·         Design software noise filtering algorithms to enhance signal and reduce noise in MLSO data. Investigate the applicability of existing community software packages for removing atmospheric effects from the MLSO data.

·         Develop visualization tools for combining MLSO data with other ground-based and NASA data products and with model output for community use.

·         Create software to automatically detect solar activity, such as solar flares, in MLSO data. Modify existing coronal mass ejection (CME) detection software to work with a variety of MLSO images and use tools like machine learning to improve CME detection.

See website for additional information on knowledge, skills, experience and education requirements and to apply for this position:

For this position:  https://ucar.wd5.myworkdayjobs.com/en-US/UCAR_Careers/details/Associate-Data-Scientist-II_REQ-2024-171

All UCAR/NCAR positions:  https://ucar.wd5.myworkdayjobs.com/en-US/UCAR_Careers/details/Associate-Data-Scientist-II_REQ-2024-171/apply