The Unidata Program Center's two summer student interns — Ana Castaneda Montoya from the University of Michigan and Leo Matak from the University of Houston — have come to the end of their summer appointments. After a summer of dedicated work they presented the results of their projects to the UPC staff on July 31, 2024.
I would like to begin by saying that this internship has definitely been one of the top highlights of my Ph.D. journey. I spent most of my working hours implementing the idea of server-side virtual data processing. This means that data on the THREDDS Data Servers (TDS) could be virtually processed without actually modifying the data. As such, the data integrity would remain intact, but it could be optimized for ML/AI.
The fifth NOAA AI Workshop on Leveraging Artificial Intelligence in Environmental Sciences will be held September 19–21, 2023 as a virtual gathering coordinated by the NOAA Center for Artificial Intelligence.
The Unidata Program Center's three summer student interns — Jhamieka Greenwood from Florida State University, Erin Rhoades from Metropolitan State University of Denver, and Jessica Souza from Texas Tech University — have come to the end of their summer appointments. After a summer of dedicated work they presented the results of their projects to the UPC staff on July 27, 2023. You can find videos of their presentations to the UPC staff on the Unidata Seminar Series page.
This summer, I had a fantastic time as a Unidata intern, strengthening my Python and data visualization skills. Even though my internship was fully remote, I was still able to have a great experience and attend many events at UCAR. My mentor, Thomas Martin, and the rest of the Unidata staff were very helpful and always available for guidance during my time with Unidata.
During my internship, I worked with the Unidata THREDDS team. My intentions this summer were to learn Java, improve my coding skills, and have experience using it in real world applications. I began my journey by converting existing unit tests for the netCDF-Java library, which is tightly linked to the THREDDS Data Server (TDS) code, to the JUnit Java testing framework. Once I got this practice with Java and had a working development environment, I was able to start working on my summer project.
Unidata is looking for an Artificial Intelligence/Machine Learning (AI/ML) developer to join our team, helping educators and students learn how to use Unidata software and data services to support their scientific research.
In this role, you'll interact with Unidata's community of researchers and educators to determine how they are harnessing AI/ML approaches to data analysis, and work toward a convention for storing data and metadata in an AI/ML ready way. In addition, you'll help evaluate existing tools such as the MetPy and Siphon python libraries and the netCDF libraries for fitness in the context of AI/ML applications. Your work will help identify and implement improvements that allow for smoother integration of Unidata software into a modern AI/ML pipeline.
