The NSF NCAR Advanced Study Program (ASP) is pleased to announce that they are now accepting applications from graduate students for the 2025 Graduate Visitor Program.
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Applications Now Open for NSF NCAR Graduate Visitor Program
17 September 2024
The NSF NCAR Advanced Study Program (ASP) is pleased to announce that they are now accepting applications from graduate students for the 2025 Graduate Visitor Program.
[Read More]16 September 2024
NOAA's Satellite Products and Services Division is looking for feedback on community use of the GOES Rebroadcast system (GRB).
[Read More]NSF Unidata Welcomes New committee Members
09 September 2024
The NSF Unidata Program Center is pleased to welcome new members to the program's governing committees. Committee members serve three-year terms, meeting twice each year to provide feedback on the effectiveness of the NSF Unidata Program and advise staff on issues facing the university community. Appointments reflect the range of large and small colleges and universities with undergraduate and graduate emphases where Unidata systems are in use.
[Read More]NSF Unidata at the 2024 Earth Educators' Rendezvous
15 July 2024
NSF Unidata is at the 2024 Earth Educators' Rendezvous in Philadelphia, PA the week of July 15-19, 2024. Join Instructional Designer Nicole Corbin and AI/ML Software Engineer Thomas Martin on Friday's poster session to discuss their ongoing collaboration with Metropolitan State University of Denver, Machine Learning Foundations and Applications in the Earth Systems Sciences.
[Read More]New eLearning: Machine Learning Foundations in the Earth Systems Sciences
12 July 2024
Announcing a new eLearning module available now on Unidata eLearning: Machine Learning Foundations in the Earth Systems Sciences. This no-code module is designed to guide you through the very basics of supervised machine learning in the Earth Systems Sciences. You will discover how machine learning is currently being used by scientists, examine the process for supervised machine learning model development, explore how data plays a crucial role in making good predictions, and how to be an effective and ethical user of machine learning tools. You will also learn that machine learning is not a catch-all solution to every problem!
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