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May22
2017

2017 Undergraduate Internship Program

May 22 - August 04, 2017

During this 11-week program NEON hosts undergraduate interns who work on projects from helping design sensor assemblies to testing sampling protocols to analyzing data. Interns work alongside staff mentors; and explore career options in weekly professional development seminars and networking events with interns from other scientific programs based in Boulder, CO. 

Key 2017 Dates

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Jun16
2017

Request for Information - NEON Bioarchive

June 16, 2017

The NEON Project is reaching out to the archival community to gauge interest in supporting the long-term archival needs for the project. 

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Jun19
2017

2017 Data Institute

June 19 - 24, 2017

This course provides critical skills and foundational knowledge for graduate students and early career scientists working with heterogeneous spatio-temporal data to address ecological questions. Our 2017 Institute focuses on remote sensing of vegetation using open source tools and reproducible science workflows – the primary programming language will be Python. 

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Jul23
2017

2017 IEEE International Geoscience and Remote Sensing Symposium

July 23 - 28, 2017

Join us for an airborne remote sensing tutorial at IGARSS 2017 

The tutorial (tutorial FD5 on IGARSS 2017 website) will include several speakers who will detail the design, implementation and lessons learned in reaching operational capacity of the Airborne Observation Platform (AOP) to support NEON.

Talks will focus on the following:

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Aug06
2017

NEON @ ESA: Working with Time Series in R using NEON Data Workshop

August 06, 2017

The temporal scale of ecological research is expanding given increased continental and global availability of time series data coming from long term data collection efforts such as NEON, LTER and Fluxnet. Given increased data availability, there is a need to implement efficient, well-documented and reproducible workflows in tools like R. In this workshop, work with NEON scientists to learn how to import, manipulate, format and plot time series data stored in .csv format in R while working with NEON data.

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