Pandora Research Graduate Intern

LLNL

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profile Job Location:

Livermore, CA - USA

profile Monthly Salary: Not Disclosed
Posted on: 30+ days ago
Vacancies: 1 Vacancy

Job Summary

We have an opening for a current graduate student to engage in an in-person 6-month long research experience related to the Pandora Small Satellite mission. Pandora will collect visible and near infrared observations of a sample of nearby exoplanets and will study both the planet atmosphere and the host star variability using long time baseline observations. The Pandora mission is funded by the NASA Pioneers program and is a collaboration between NASA Goddard Space Flight Center Lawrence Livermore National Laboratory NASA Ames Research Center and a host of other research and university institutions.

This opportunity comes with a significant time allocation on LLNLs world-leading high-performance computing platforms so is particularly well suited for a student with interests in compute-intensive modelling and simulation projects. There will be also opportunities to directly interface with the Pandora engineering team based at LLNL and the potential to work on science projects closely related to instrumentation.

The graduate student will work under the supervision of an LLNL scientist within the Pandora collaboration on a project related to Pandora core science or auxiliary science. The specific project topic is flexible and can be designed to align with the students research interests and PhD thesis project. This position is in the Astronomy & Astrophysics Analytics Group within the Physics Division.

Applications for this opportunity are due by December 15th 2025. Applicants should upload a CV a brief statement of research interests and provide the details of two references. The start date for this opportunity is flexible but can be no later than March 30th 2025.

Depending on your assignment this position may offer a hybrid schedule blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.

You will

  • Work with LLNL scientists and engineers conducting research and development on the Pandora Small Satellite.
  • Have the opportunity to learn techniques related to high performance computing systems and cutting-edge statistical inference and modeling methods.
  • Have the opportunity attend weekly talks at LLNL including the Space Science Institute seminar series.
  • Interact with a broad spectrum of scientists and engineers internally at LLNL.
  • Conduct research in assigned area under limited direction and supervision.
  • Perform scientific assignments at an appropriate level of complexity and work collaboratively on scientific research and development projects.
  • Analyze results and provide weekly updates to the Pandora collaboration
  • Present work through oral presentations and/or poster sessions.
  • Perform other duties as assigned.

Qualifications :

  • Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA).  See Additional Information section below for details.
  • Must be a continuing PhD student in good standing at an accredited institution pursuing a graduate degree.
  • Demonstrated academic achievement in astrophysics via peer-reviewed publications
  • Effective communication skills.
  • Ability to present and communicate concepts and ideas.
  • Ability to work in a team environment.

Qualifications We Desire

  • Experience with modern high-performance computing systems
  • Familiarity with the science goals and requirements of the Pandora mission
  • Experience with Gaussian process models and Bayesian inference libraries
  • Experience with automatic differentiation programming frameworks such as JAX

Additional Information :

#LI-Hybrid

Why Lawrence Livermore National Laboratory

We have an opening for a current graduate student to engage in an in-person 6-month long research experience related to the Pandora Small Satellite mission. Pandora will collect visible and near infrared observations of a sample of nearby exoplanets and will study both the planet atmosphere and the ...
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Key Skills

  • Robotics
  • Machine Learning
  • Python
  • AI
  • C/C++
  • Data Collection
  • Research Experience
  • Signal Processing
  • Natural Language Processing
  • Computer Vision
  • Deep Learning
  • Tensorflow

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