Post-Doctoral Associate in Machine Learning for Space Weather (University of Colorado, Boulder)
The Cooperative Institute for Research in Environmental Sciences (CIRES) encourages applications for a full-time Post-Doctoral Associate to work on the development, validation, and calibration of space weather models, using machine learning and physics-based models. This position contributes to a NASA-funded project within the ‘Space Weather with Quantified Uncertainty’ program. The main objective will be to deliver probabilistic space weather forecasts with their associated uncertainties. In particular, this position will focus on the forecast of solar wind quantities (speed and magnetic field). The position will involve close collaboration with other post-docs, students, and senior members of the project, which are divided between CIRES, the Computer Science Department and the Space Weather Technology, Research, and Education Center (SWx-TREC) at CU Boulder, and the space physics group at the University of California, Los Angeles. The position will be primarily based at CU Boulder, although remote working can be considered.
Apply here: https://jobs.colorado.edu/jobs/JobDetail/?jobId=37501
enrico.camporeale@noaa.gov
Postdoctoral Research Associate (University of New Hampshire)
This postdoc will apply big data and machine learning techniques to several decades of ground and space observations to improve our understanding and predictions of geomagnetically induced currents. The postdoctoral research is part of a 4-year, 4-million-dollar project conducted in partnership between the University of New Hampshire and the University of Alaska-Fairbanks (UAF). The postdoc will also have the opportunity to be involved in the space weather underground program (SWUG) that works with local high school students to build, deploy, and analyze ground magnetometers. Candidates with experience in machine learning and/or ground magnetometer data analysis are particularly encouraged to apply.
Apply here: https://jobs.usnh.edu/postings/46205
amy.keesee@unh.edu