CIRES/NOAA NCEI Research Scientist – Magnetic Navigation & Machine Learning
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Job Summary
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), invites applications for a Research Scientist position for Magnetic Navigation. MagNav is a navigation technology that leverages Earth’s natural magnetic field to enhance global navigation resilience in GPS-denied environments. A key aspect of MagNav is the development of accurate magnetic maps and estimating the associated uncertainties. The successful candidate will join a cutting-edge project aimed at developing geomagnetic anomaly maps and advancing the use of machine-learning techniques for MagNav. The research outcomes will support navigation applications and provide valuable tools for government, industry, and academia.
This CIRES position is based at the David Skaggs Research Center in Boulder, Colorado, and offers a hybrid work option.
Who We Are
At CIRES, more than 950 environmental science professionals work to understand the dynamic Earth system, including people’s relationship with the planet. CIRES has partnered with NOAA since 1967, and our areas of expertise include weather and climate, changes at Earth’s poles, air quality and atmospheric chemistry, water resources, solid Earth sciences, and more. Our vision is to be instrumental in ensuring a sustainable future environment by advancing scientific and societal understanding of the Earth system.
NOAA’s National Centers for Environmental Information (NCEI) is responsible for hosting and providing access to one of the most significant archives on Earth, with comprehensive oceanic, atmospheric, and geophysical data. From the depths of the ocean to the surface of the sun and from million-year-old sediment records to near real time satellite images, NCEI is the Nation’s leading authority for environmental information.
The CIRES/NCEI geomagnetism team conducts basic and applied research in the field of Earth magnetism. We develop data-based models and calculators of the various magnetic fields originating within the Earth (in the core, mantle, lithosphere and oceans) and in the near-Earth space environment (in the ionized layers of the atmosphere and the magnetosphere). Such models have a wide range of scientific and technical uses, from investigating physical processes associated with a particular source, for example core flows, to providing accurate headings for aircraft navigation and directional drilling. The group is based out of NOAA's Boulder campus and is primarily funded by the NOAA National Centers for Environmental Information (NCEI) through an agreement with the National Geospatial-Intelligence Agency (NGA).
What Your Key Responsibilities Will Be
- 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%)
What You Should Know
- Due to the requirement to access export-controlled data and information, only U.S. citizens, lawful permanent residents (green cards), or other protected individuals (i.e., persons designated as an asylum, refugee, or a temporary resident under amnesty provisions) may apply.
- If you are the selected finalist, you will be required to successfully complete a federal background clearance process for site access.
- 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.
What We Can Offer
- CIRES can offer a generous compensation package.
- The annual hiring salary range for this position is $72,000 - $93,992.
- Salary is commensurate with education and experience and determined based on our CIRES internal career track classification.
- Some relocation funds are available for this position to off-set moving expenses following CIRES and the University of Colorado’s relocation processes and procedures.
- This position can accommodate a hybrid work modality.
- CIRES and the University of Colorado Boulder offer a robust training curriculum, opportunities for professional development and a Mentorship Program.
- Boulder is a vibrant community with access to mountain parks, dog parks, miles of trails, rivers, lakes, cafes, restaurants, boutiques, theaters, museums, and sports venues. Boulder was recently ranked as one of the top places to live in the U.S. by U.S. News.
- As an employee at CU Boulder, you receive a pass allowing free access to the regional public transit system, which is an outstanding network of buses and light rail systems that provide service within Boulder and connect to Denver, the Denver airport, and surrounding communities.
Benefits
Be Statements
What We Require
- 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
What You Will Need
- 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.
What We Would Like You to Have
Please note that while the position details both required and preferred skills and experience, we invite applicants to apply even if they do not have the preferred skills and experience outlined in this section. If you meet the requirements and have passion for the work, you are encouraged to apply. We encourage on the job training for any additional skills or knowledge that become relevant to the position.
- 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.
Special Instructions
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. Please note that a cover letter is mandatory and applicants who do not submit this document at the time of application will not be considered.
- Although not required at the time of application, please be ready to offer contact information for professional references who can be contacted on your behalf if you are identified as a finalist for this role. We will use a digital reference check solution.
If you are selected as the finalist, your degree will be verified by the CU Boulder Campus Human Resources department using an approved online vendor. If your degree was obtained outside of the United States, please submit a translated version (if applicable) as an optional attachment.
This position will close on December 13, 2024.
Note: Application materials will not be accepted via email. For consideration, applications must be submitted through CU Boulder Jobs.
Posting Contact Information
Posting Contact Name: Manoj Nair
Posting Contact Email: manoj.c.nair@noaa.gov