JOB OPENING: Space Physicist in Machine Learning and Space Weather

September 1, 2019, from Richard Morton

OPENING: Space Physicist in Machine Learning and Space Weather
From: Paul Loto’aniu (paul.lotoaniu at

The Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado Boulder has an immediate opening for a Space Physicist. This position supports NOAA’s National Centers for Environmental Information (NCEI) in work related to the magnetometers (MAG) on the GOES-R mission satellites. The physicist will develop machine learning techniques for satellite data correction algorithms and for space weather research. The position is initially for one year, with up to two additional years depending on performance and availability of funding. The Geostationary Operational Environmental Satellite Series-R (GOES-R) is NOAA’s next generation of geostationary weather satellites, which include a complement of space weather sensors to monitor the local space environment and the Sun. Two of the GOES-R satellites have been launched and are now called GOES-16 and GOES-17.

A Masters or Ph.D. in a hard science, mathematics, or statistics with an emphasis on machine learning, statistics, space physics, astrophysics, geophysics, or, similar scientific discipline. Extensive experience in time-series analysis. Knowledge of Python, IDL, Matlab or other high-level programming languages.

Experience using TensorFlow, Torch, Theano, Caffe, Neon, the IBM Machine Learning Stack or similar frameworks. Research or course work in Machine Learning (ML), Research or course work in space physics, Understanding of magnetospheric physics and/or the geomagnetic field, Experience working with spacecraft science data, Experience using cloud services such as AWS.

Apply at:

For further information contact Dr. Paul Loto’aniu (