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Ocean Modeling Data Assimilation Researcher

Responsibilities

Peraton is seeking a Ocean Modeling Data Assimilation Researcher at Stennis Space Center in MS.  The ocean has historically been under-observed, and thus instruments are steadily being designed to provide more observations with higher resolution in both space and time. One such instrument is NASA’s wide-swath Surface Water and Ocean Topography (SWOT) altimetry satellite which will provide sea surface height (SSH) observations at a 1-2km spatial resolution within a ~120km wide swath over a 21 day repeat orbital cycle. This unprecedented high spatial resolution poses a challenge to the Navy’s current operational data assimilation (DA) systems, which were designed for sparse datasets.

 

This project will perform direct SSH assimilation using NCODA-4DVAR in an operational, Navy relevant domain. The capability of a 4DVAR system to correct over time and space, along with the dynamics of the ocean model, will allow information from assimilated SSH observations to propagate to the subsurface by the dynamics of the tangent linear and adjoint of the model. The advantage of this approach is a substantial increase in the number of SSH observations assimilated into the model, which will significantly impact the accuracy of our ocean forecasts.

 

Responsibilities will include:

  • Change NCODA schema for processing SSH observations to account for temporal density over a time window as opposed to a single time.
  • Develop a procedure one for computing the mean model SSH.
  • Develop a procedure for online de-tiding of the model.
  • Evaluate the direct assimilation of SSH observations within a 4DVAR DA system, creating a substantial increase in the number of SWOT SSH observations utilized, and applying the increase of temporally and spatially dense SSH observations assimilated to reduce the error within an ocean forecast.
    • Measured the number of SSH observations assimilated using the new method and compare against the number of SSH observations used in the current operational method through Improved Synthetic Observation Profiles (ISOP).
    • Assess the accuracy of forecasts produced by direct SSH assimilation by examining the Root Mean Square Error against a forecast produced with ISOP.
    • Investigate the effects on computational expense when implementing direct SSH assimilation.
  • Present results at academic conferences.
  • Publish results in peer reviewed journals.

Qualifications

PhD in Mathematics or an Applied Science Field

  • Must have coding experience in MATLAB, Python, Fortran, and Julia.
  • Must have experience with Linux, Shell Scripting, VSCode, and High Performance Computing (HPC).
  • Must be knowledgeable in Numerical Methods, Data Analysis, Data Assimilation, Ocean Modeling.
  • Must be familiar with U.S. Navy standard ocean models.
  • Must have the ability to obtain a Secrete Clearance
  • Experience working in a Department of Defense research facility strongly preferred.

Peraton Overview

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world’s leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can’t be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we’re keeping people around the world safe and secure.

Target Salary Range

$66,000 - $106,000. This represents the typical salary range for this position based on experience and other factors.

EEO

EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.

Average salary estimate

$86000 / YEARLY (est.)
min
max
$66000K
$106000K

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What You Should Know About Ocean Modeling Data Assimilation Researcher, Peraton

If you're ready to dive into the world of ocean modeling, Peraton has an exciting opportunity for you! We’re on the lookout for an Ocean Modeling Data Assimilation Researcher at the Stennis Space Center in MS. This role is all about harnessing the power of advanced data assimilation techniques to improve our understanding and forecasting of ocean dynamics, particularly in relation to the innovative data being gathered by NASA’s SWOT altimetry satellite. These SSH observations at high spatial resolutions of 1-2 km are set to transform oceanic data collection, and we need your expertise to effectively integrate this influx of information into Navy operational data practices. You will be working on adapting NCODA-4DVAR to assimilate SSH observations seamlessly and evaluate its effectiveness in increasing forecast accuracy. Your tasks will include fine-tuning the data processing schema, developing new methodologies for SSH modeling, and rigorously assessing forecast errors compared to current processes. Plus, you’ll get the chance to present your findings at academic conferences and publish your research in esteemed journals. With a PhD in Mathematics or a related field required, alongside coding skills in MATLAB, Python, Fortran, and Julia, this position offers a thrilling challenge for those ready to contribute to enhancing the accuracy of ocean forecasts. Join us at Peraton and help us tackle some of the most critical challenges facing our oceans today!

Frequently Asked Questions (FAQs) for Ocean Modeling Data Assimilation Researcher Role at Peraton
What responsibilities does an Ocean Modeling Data Assimilation Researcher at Peraton have?

As an Ocean Modeling Data Assimilation Researcher at Peraton, you will be tasked with enhancing the Navy's data assimilation systems to effectively integrate SSH observations from the SWOT satellite. This includes adapting the NCODA schema for better processing of SSH data, developing methodologies for online de-tiding of the model, and increasing the number of SSH observations assimilated into the operational forecast. You'll also work on evaluating the impact of these advancements on forecast accuracy and computational efficiency.

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What qualifications are needed for the Ocean Modeling Data Assimilation Researcher position at Peraton?

To qualify for the Ocean Modeling Data Assimilation Researcher role at Peraton, candidates should hold a PhD in Mathematics or an Applied Science Field. Additionally, experience with programming languages such as MATLAB, Python, Fortran, and Julia is essential. Candidates must also be knowledgeable in Numerical Methods, Data Analysis, and Ocean Modeling. Familiarity with U.S. Navy standard ocean models and experience in a Department of Defense research facility are preferential.

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How does Peraton support professional development for Ocean Modeling Data Assimilation Researchers?

At Peraton, we highly value the growth of our employees. As an Ocean Modeling Data Assimilation Researcher, you'll have opportunities to present research findings at academic conferences and publish in peer-reviewed journals. We encourage continuous learning and development, ensuring you have access to resources and training that can further enhance your skills and expertise in the field.

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What programming skills are essential for the Ocean Modeling Data Assimilation Researcher role at Peraton?

The Ocean Modeling Data Assimilation Researcher position at Peraton requires solid programming skills in MATLAB, Python, Fortran, and Julia. Additionally, proficiency with Linux, Shell Scripting, and High-Performance Computing (HPC) is critical for successfully managing and analyzing large datasets from ocean models.

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Why is data assimilation important for the Ocean Modeling Data Assimilation Researcher at Peraton?

Data assimilation is crucial for the Ocean Modeling Data Assimilation Researcher role at Peraton as it enhances the accuracy and reliability of ocean forecasts. By effectively integrating high-density SSH observations from sources like NASA's SWOT satellite, researchers can significantly improve the understanding of ocean dynamics, ultimately benefiting operational strategies and the broader marine research community.

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Common Interview Questions for Ocean Modeling Data Assimilation Researcher
Can you explain your experience with data assimilation in ocean modeling?

In your answer, detail specific projects you've worked on involving data assimilation. Mention particular techniques you’ve employed, such as NCODA or other 4DVAR systems, and highlight any challenges you faced and how you overcame them to improve forecast accuracy.

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What programming languages are you most proficient in, and how have you used them in ocean modeling?

Specify the programming languages you master, like MATLAB and Python. Provide examples of projects where you utilized these languages to manipulate data, build models, or conduct simulations, emphasizing how they contributed to your research outcomes.

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Describe a time you had to adapt a method for processing ocean data. What was the outcome?

Share a concrete example illustrating how you adapted or redesigned a data processing method. Highlight your analytical approach, the methods you modified, and the positive impact this had on the overall data assimilation process.

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How would you evaluate the effectiveness of a new assimilation method?

Discuss various metrics and validation techniques you would use to assess the accuracy of the new assimilation method. Mention the importance of RMSE comparisons, forecast skill scores, and any relevant statistical analysis that would support your evaluation.

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What are the challenges of assimilating high-density SSH observations?

Talk about potential issues such as computational expense, algorithm complexity, and data sparsity challenges. Explain how you would address these challenges using innovative strategies or methodologies in your work.

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How do you stay current with advancements in ocean modeling and data assimilation?

Share the steps you take to keep abreast of the latest research and technologies, such as attending conferences, reading journals, participating in online workshops, and engaging with the academic and professional community focused on oceanography and data assimilation.

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What do you find most rewarding about working in ocean modeling?

Discuss your passion for ocean science and research. Reflect on meaningful experiences where your work positively impacted understanding or mitigation of ocean issues, demonstrating your commitment to the field.

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Can you give an example of how you've collaborated with a team on a research project?

Elaborate on your collaborative experiences, focusing on a specific project where teamwork was crucial. Highlight your role, the nature of the collaboration, and how your combined efforts led to successful research outcomes.

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Why do you want to work for Peraton as an Ocean Modeling Data Assimilation Researcher?

Share your motivations for wanting to join Peraton, referencing the company's commitment to national security and innovative approaches to ocean science. Align your career goals with their mission and values, making it clear how you see yourself contributing to their projects.

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What is your approach to presenting complex data and findings to non-technical stakeholders?

Outline your strategies for simplifying complex models and data sets. Emphasize the importance of clarity and visualization tools in your presentations, demonstrating your ability to communicate effectively with diverse audiences.

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April 21, 2025

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