CIRES/NOAA NCEI Research Scientist Magnetic Navigation & Machine Learning

$72,000 - $93,992/Yr

University of Colorado - Boulder, CO

Full-time - Entry Level

Boulder, CO

501-1,000 employees

Educational Services

About the position

The Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado Boulder, in partnership with NOAA's National Centers for Environmental Information (NCEI), is seeking a Research Scientist specializing in Magnetic Navigation and Machine Learning. This role focuses on developing geomagnetic anomaly maps and utilizing machine learning techniques to enhance navigation technologies in GPS-denied environments. The successful candidate will contribute to a cutting-edge project that supports navigation applications across government, industry, and academia, while also promoting an inclusive and diverse work environment.

Responsibilities

• Develop and implement machine learning algorithms to improve Earth's magnetic anomaly maps and models (30%)
• Investigate the use of non-traditional datasets to improve the resolution and accuracy of geomagnetic maps (10%)
• Collaborate with the U.S. National Geospatial-Intelligence Agency (NGA) and other stakeholders to share research findings (10%)
• Identify and address critical research questions related to a full understanding of crustal magnetic anomalies, analyzing large geophysical datasets (30%)
• Publish research in peer-reviewed journals and present findings at scientific conferences (10%)
• Seek and secure funding for continued research in geomagnetic field modeling and associated technologies from agencies such as NASA, NOAA, and others (10%)

Requirements

• PhD in physics, geophysics, applied mathematics, engineering, computer science, or related fields
• Experience in machine-learning applications with strong programming skills in Python or MATLAB
• At least 1 year of post-doctoral research
• Expertise in processing physical or geophysical data
• Experience applying machine learning techniques to physical or geophysical data, especially in anomaly detection or prediction
• Ability to communicate research findings effectively in English, both in writing and presentations
• Capability to contribute to a collaborative and inclusive team environment
• Proven capability for self-guided, motivated, and original research

Nice-to-haves

• Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar
• Experience in optimizing software to reduce memory usage and increase performance
• A willingness to learn from teammates

Benefits

• Dental insurance
• Health insurance
• On-the-job training
• Paid time off
• Tuition benefit
• ECO Pass