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.

Unidata is looking for graduate and undergraduate students in the geosciences to share their views on remote learning environments. The Unidata Users Committee and Unidata Program Center staff want to hear about your experiences, needs, and wishes for remote learning during a special online discussion session.

The panel discussion will be held be from 1:00 to 1:55 PM MST on November 13, 2020. We're hoping to have roughly six students representing a variety of atmospheric science and related programs share their thoughts about what works well in remote learning situations, what doesn't work, and what might be done to improve the experience. Each student will have a short opportunity (3-4 minutes) to share their experience, followed by a dialogue with the Users Committee. A synthesis of the discussion will be shared with the Unidata community to communicate lessons learned.

Unidata developer Ryan May is a co-PI on a recently-awarded grant by the National Science Foundation's EarthCube program. The grant, which brings together collaborators from Unidata, NCAR's Computational & Information Systems Laboratory (CISL), NCAR's Climate and Global Dynamics Laboratory (CGD), and the University at Albany, SUNY, funds Project Pythia: A Community Learning Resource for Geoscientists.

Project Pythia aims to provide web-accessible training to help current and future geoscientists understand and use the ever-expanding volume of numerical scientific data. The project will leverage Jupyter Notebooks as the primary delivery mechanism for training examples, curricula, and as an interactive computing platform. The content for Project Pythia will be hosted on GitHub and maintained using an Open Development model that will facilitate and encourage contributions from a broad user community, as well as help ensure the long-term sustainability of the project.

The Unidata Program Center is hiring! We are looking for an educational designer to join our team, helping educators and students learn how to use Unidata software and data services to support their scientific research.

You'll help us help our community of scientists access the Earth system science data that fuels their research. You'll have a chance work with a great team at the Unidata Program Center and and enthusiastic open source community to develop interactive learning materials and training experiences on topics related to Unidata scientific software packages and programming.

MetPy 1.0 Release Candidate 2 has been released. The biggest change is that now XArray DataArrays can be returned from most calculations when they are passed as inputs (this may break some code not expecting this behavior). This is the final planned release candidate before the full 1.0 release (planned in about a month), so any testing and feedback is appreciated, especially in the DataArray support. We should also have a 1.0 upgrade guide available soon in the documentation.