Graduate Research Scientist intern

Posted 3 Days Ago
Be an Early Applicant
Hiring Remotely in New Jersey, USA
Remote
28-34 Hourly
Internship
Aerospace • Information Technology • Professional Services • Analytics
The Role
Graduate‑level internship supporting cryospheric remote‑sensing research: extend RTM‑SciML to polarized radiance, generate synthetic Stokes vector datasets with vector RT models, train/evaluate ML retrievals for albedo and melt pond fraction, assess instrument tradeoffs, and produce documentation and recommendations.
Summary Generated by Built In

Job Description:

AMA is seeking a graduatelevel Research Scientist intern to support cryospheric remotesensing research at NASA Langley Research Center (LaRC), contributing to a feasibility study that integrates multiangle polarimetry, radiative transfer modeling, and machinelearningbased retrievals to advance instrument concept development for future Earthobserving missions.

The hourly rate for this position is $27.69-$33.85 determined by level of education and relevant skills and experience. Remote work is an option.

Key Responsibilities

  • Conduct a feasibility analysis for a passive multi‑angle polarimeter designed to retrieve sea ice albedo and related cryospheric variables.

  • Extend the published RTM‑SciML framework (Zhou et al., 2023, 2025) to incorporate polarized radiance and dense angular sampling.

  • Produce a synthetic training dataset of top‑of‑atmosphere Stokes vectors using a vector radiative transfer model across representative sea ice surface conditions.

  • Train and evaluate ML models to retrieve broadband shortwave albedo and melt pond fraction.

  • Quantify retrieval performance across spectral, angular, and polarimetric configurations using held‑out synthetic test data.

  • Document trade‑offs between spectral range, angular sampling, and polarimetric capability.

  • Deliver recommendations for multi‑angle polarimeter instrument design.

  • Prepare clear documentation, written reports, and oral presentations summarizing methods and findings.

Required Qualifications

  • Bachelor’s in Physics, Atmospheric Science, or a related field.

  • Strong Python skills, including NumPy and SciPy.

  • Experience with a machine learning library such as PyTorch or TensorFlow.

  • Ability to work with large multi‑dimensional scientific datasets.

  • Experience with radiative transfer modeling; familiarity with vector RT codes such as AccuRT, libRadtran, SCIATRAN, or VLIDORT.

  • Ability to work independently and document code and methodology clearly.

  • Strong written and oral communication skills.

Desired Qualifications

  • Background in atmospheric or cryospheric remote sensing.

  • Experience or coursework related to optical instrument design or polarimetry.

  • Familiarity with polarimetric measurements and their applications.

  • Interest in contributing to a peer‑reviewed publication.

  • Enthusiasm for instrument concept development for current and future Earth‑observing missions.


Analytical Mechanics Associates (AMA) is proud of our customer relationships, our diverse and dynamic work environment, and our employees' career satisfaction. AMA is a small business with a wide reach; headquartered in Hampton, VA, AMA has operations in Greenbelt, MD; Huntsville, AL; Dallas and Houston, TX; Denver, CO; Mountain View, CA; and Edwards Air Force Base, CA. With over 60 years of experience, AMA specializes in aerospace engineering, science, analytics, information technology, and visualization solutions. AMA combines the best of engineering, science, and mathematics capabilities with the latest in information technologies, visualization, and multimedia to build creative solutions. We offer competitive salaries and a substantial benefits package, including but not limited to paid personal and federally recognized holiday leave, salary deferrals into a 401(k)-matching plan with immediate vesting, tuition reimbursement, short/long term disability plans, and a variety of medical, dental, and vision insurance options.
AMA is committed to the professional growth of every employee, understanding that the successes of our employees drive our success. We provide a work environment that is engaging, collaborative, and supportive. To learn more about our company, please visit our website at www.ama-inc.com/careers and follow us on Facebook and LinkedIn.


AMA is an Equal Opportunity Employer and does not discriminate against any applicant for employment or employee because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic prohibited under federal, state, or local laws.

Skills Required

  • Bachelor's in Physics, Atmospheric Science, or related field.
  • Strong Python skills, including NumPy and SciPy.
  • Experience with a machine learning library such as PyTorch or TensorFlow.
  • Ability to work with large multi-dimensional scientific datasets.
  • Experience with radiative transfer modeling; familiarity with vector RT codes such as AccuRT, libRadtran, SCIATRAN, or VLIDORT.
  • Ability to work independently and document code and methodology clearly.
  • Strong written and oral communication skills.
  • Background in atmospheric or cryospheric remote sensing.
  • Experience or coursework related to optical instrument design or polarimetry.
  • Familiarity with polarimetric measurements and their applications.
  • Interest in contributing to a peer-reviewed publication.
  • Enthusiasm for instrument concept development for Earth-observing missions.
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The Company
453 Employees
Year Founded: 1962

What We Do

Since 1962, Analytical Mechanics Associates (AMA) has worked with government and commercial organizations solving tough engineering, math, and business problems. The company combines the best of engineering, science, and mathematics capabilities with the latest in information technology and visualization to build innovative solutions. The knowledge, innovation, and dedication of the AMA team creates solutions for today’s problems and provides a catalyst for tomorrow’s discoveries.

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