The Cooperative Institute for Research in Environmental Sciences (CIRES) encourages applications for a full-time Postdoctoral Associate to work on the development, validation, and calibration of space weather models, using models based on machine learning and physics. This position contributes to a NASA-funded project within the ‘Space Weather with Quantified Uncertainty’ program.
Mar. 22, 2022 1:45 pm
Deadline for application
Apr. 22, 2022 5:00 p.m.
The Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado Boulder
The Cooperative Institute for Research in Environmental Sciences (CIRES) encourages applications for a full-time Postdoctoral Associate to work on the development, validation, and calibration of space weather models, using models based on machine learning and physics. 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 forecasting solar wind quantities (speed and magnetic field). The position will involve close collaboration with other postdocs, students, and senior members of the project, which is divided between CIRES, the Department of Computer Science, 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. Position will be based primarily at CU Boulder, although remote work may be considered.
The University of Colorado Boulder is committed to building a culturally diverse community of faculty, staff, and students dedicated to contributing to an inclusive campus environment. We are an equal opportunity employer, including veterans and people with disabilities.
At CIRES, more than 800 environmental scientists work to understand the Earth’s dynamic system, including the relationship of people to the planet. CIRES is a partnership of NOAA and CU Boulder, and our areas of expertise include weather and climate, Earth’s pole shifts, air quality and atmospheric chemistry, water resources, and hard Earth science. . Our vision is to be instrumental in ensuring a sustainable future environment by advancing scientific and social understanding of the Earth system.
- Develop a set of machine learning models for application to the prediction of specific space weather phenomena and relevant parameters (i.e., the solar wind magnetic field).
- Calibrate those models to get meaningful probabilistic predictions.
- Validate models, including comparison to physically based models.
- Actively participate in other research activities within the project, possibly co-supervising students.
- Publish articles in international scientific journals and present results at scientific congresses
- Doctor. in Physics, Mathematics, Computer Science or related careers.
- Experience in Machine Learning, Bayesian Methods and Big Data analysis.
- Experience in computer programming with Python (or similar) and the ability to generate distributable code.
- An understanding of the physics of space weather, such as solar wind propagation or the geospatial current system.
- Analysis of solar, magnetospheric and solar wind data.
- A proven track record of conducting independent research, writing scientific papers, and presenting results at conferences.
- A mindset for transformative research.
To apply, please submit the following materials:
- Curriculum Vitae or CV.
- Cover letter addressed to the Search Committee that briefly describes your qualifications, career goals, and specific interest in this position.
- A representative and significant scientific publication.
- List of contact information for 3 references who will be willing to write a confidential letter of recommendation for you. If you are identified as a finalist, the search committee will request letters of recommendation on your behalf.
Review of applications will begin on April 15, 2022. The position will remain open until filled.
Use this link to apply: CIRES Postdoctoral Associate in Machine Learning for Space Weather (colorado.edu)
Publication of contact information
Post Contact Name: Enrico Camporeale
Post Contact Email: [email protected]