As part of my summer of 2024 internship I had the privilege of getting involved with some of NSF Unidata's Python projects. My work ranged from creating educational tutorials to adding new functionalities to existing libraries, enhancing the resources available to the community.
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.
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.
