The successful applicant will participate on a team of LDEO researchers and external collaborators as part of the Lamont Real Time Earth (RTE) strategic initiative. The analysis will write python code to assist in downloading, organizing, transforming, and catalog data sets from TRACMIP, CMIP6, and other data archives and perform uploads to cloud storage. In the process, they will be expected to contribute to existing open source software projects such as intake, zarr, and xarray. They will also develop examples and tutorials to demonstrate how to access these data in the cloud and perform common analysis tasks. Finally, they will help administer the LDEO RTE program and provide technical support to the part time staff.
Download, organize, catalog, and upload data sets for Pangeo cloud datastore; combine netCDF files into zarr stores, resolve metadata conflicts, and verify data set integrity; develop python scripts to automate data ingestion and update process.
Develop documentation and tutorials on python data analysis tools (xarray, zarr, xgcm, etc.) motivated by RTE-related research projects. Document usage and best practices for cloud-native data storage, cloud-based environments (Pangeo), and intake catalogs.
Provide technical support to other RTE staff regarding their research projects.
Help organize and manage applications to RTE program.
Document all activities in regular blog posts
Minimum qualifications are a Bachelor's Degree in Mathematics, Computer Science, Physical Sciences, or equivalent. Successful candidate must be able to work independently with little supervision.
Prior experience with python programming and scientific data analysis.
Experience with the python libraries xarray, dask, zarr, and intake.
Basic familiarity with cloud computing (Google Cloud Platform and / or Amazon Web Services).
Equal Opportunity Employer / Disability / Veteran
Columbia University is committed to the hiring of qualified local residents.
Internal Number: 500683
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