R&D for Machine Learning and Uncertainty Quantification

Seeking motivated candidates to join a Langley Research Center team performing research & development in the areas of uncertainty quantification (UQ) and machine learning (ML). Multiple positions are expected to be filled where the focus will range from research on new UQ/ML methodologies to software engineering work on NASA UQ/ML software. All projects will have the opportunity to apply these methods and codes to challenging, real-world NASA problems. Successful candidates will be matched with specific projects based on their interests and background.

Research-focused team members will explore new approaches in areas within UQ/ML including, but not limited to: generative modeling, multifidelity UQ methods, symbolic regression, scientific ML, statistical/probabilistic approaches for inverse problems, operator learning, optimization under uncertainty, active learning, and reliability analysis. Candidates here must be knowledgeable in UQ/ML fundamentals (e.g., probability & statistics), while proficiency in Python and modern software development practices is beneficial but not required. Preference will be given to graduate students or undergraduates with research experience.

Software engineering-focused team members will work on some of NASA's open-source Python libraries (github.com/nasa/bingo, github.com/nasa/smcpy, github.com/nasa/MXMCPy) as well as non-public NASA software. Software applications may include ML, UQ, data science, high-performance computing, and high-throughput simulation. Tasks will be performed as part of a small development group that emphasizes good software engineering practices and reusable code. Candidates here must be proficient in Python; experience in other languages such as c++ may also be useful. Experience with clean coding practices, version control, software deployment, and performance optimization is beneficial. Knowledge/experience of UQ/ML will be useful but is not required for these positions.

Come make a tangible impact with NASA!

**Eligible Applicants:** All
**Academic Level:** Undergraduate Freshman, Undergraduate Sophomore, Undergraduate Junior, Undergraduate Senior, Graduate Master's, Graduate Doctoral, Post Doctoral
**Activity Type:** In-person
**Citizenship:** US Citizen Only
**Type:** Internships