CIRES/NOAA NCEI Space Physicist in Machine Learning and Space Weather

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 for three years, with extension beyond this dependent on performance, availability of funding and need. The Space Weather Team within NCEI is responsible for supporting NOAA’s space weather mission and for ensuring the operational and scientific utility of NOAA’s space environmental data. 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.


Responsibilities

Develop Machine Learning (ML) algorithms to correct data issues in GOES-R MAG by conducting a literature research of applicable ML algorithms, derive and develop the models, develop test code, extensively test the algorithms using GOES-R data, and select the best method to implement.

Undertake scientific research that demonstrates the utility of the GOES-R full 10 Hz magnetometer data. 

The research topic is open but possible area(s) of research include plasma waves research, multi-satellite data assimilation or the development of a high-resolution (1-minute or higher) magnetic field model using ML. This research will be used to inform future development of operational products through research to operations (R2O) work.

Publish scientific papers in peer-reviewed journals and present science results at science conferences.

Develop long-term data trending tools in Python to monitor MAG data quality and to detect data anomalies.

Participate in our group meetings and other meetings, as required.

Write science proposals and look for funding opportunities, as required.


What You Should Know

This position will be rostered in CIRES at the University of Colorado Boulder, but will be physically situated in the David Skaggs Research Center, 325 Broadway, Boulder, CO 80305.  If you are the selected finalist you will be required to pass a federal laboratory background clearance for site access.


What We Can Offer

We can offer a competitive salary, commensurate with experience, along with a generous benefits package.

Requirements

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.

What You Will Need

Ability to work both cooperatively within a team environment and independently.

Excellent oral and written communication skills.

What We Would Like You To Have

Experience using TensorFlow, Torch, Theano, Caffe, Neon, the IBM Machine Learning Stack or similar frameworks.

Research or course work in 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.


Benefits

The University of Colorado offers excellent benefits, including medical, dental, retirement, paid time off, tuition benefit and ECO Pass. The University of Colorado Boulder is one of the largest employers in Boulder County and offers an inspiring higher education environment. Learn more about the University of Colorado Boulder.


Application Materials

To apply, please submit the following materials:

Resume or CV

Cover letter addressed to the Search Committee briefly describing your qualifications, professional goals, and specific interest in this position. 

List of 3 references: the names, professional titles, and contact information of those who are familiar with your qualifications and work history.

If you are selected as the finalist, we will contact you through email and request that you submit the name and email of one (1) reference who will be asked to submit a letter of recommendation. This information will be kept confidential and viewable only by the search committee.

 

This position will remain open until filled.

 

Note: Application materials will not be accepted via email. For consideration, applications must be submitted through CU Boulder Jobs.

Job Number

20093

Date Posted

Monday, September 9, 2019

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