BEAST Internship
Master's-level engineering internship at the NASA Ames Research Center Arc-Jet Complex. 10 weeks building the data backbone for next-generation hypersonic test campaigns.
About BEAST
BEAST (Big-data Efficient Automated Science Transfer) is a Django-based web application that centralizes arc-jet facility data: test campaigns, diagnostic time-series, material properties, facility configurations, and ML-based predictions.
The intern will focus on HDF5 as the reference data interchange format — its self-describing, compressed, hierarchical structure makes it well-suited for large multi-channel diagnostic datasets typical of arc-jet testing. Work spans data engineering, automated reporting, technical documentation, and machine learning.
Data Engineering
HDF5 import/export pipelines for arc-jet diagnostic datasets.
Automated Reporting
LaTeX-based PDF reports generated directly from test data.
Machine Learning
Regression models predicting heat flux and enthalpy from test diagnostics.
Internship Tasks
Four structured deliverables across 10 weeks, each ending with a concrete, reviewable artifact.
HDF5 Import & Export
- Design the BEAST HDF5 schema
- Implement import & export views
- Write round-trip unit tests
Automated Reporting
- Extend the existing LaTeX report template
- Add a
generate_reportmanagement command - Wire a Generate Report button on the test-detail page
User Manual
- Add an HDF5 Data Exchange section
- Fill remaining placeholder sections
- Document API endpoints and data models
docs/.
Predictive Modeling
- Select a target variable (e.g. heat flux or enthalpy)
- Compare Linear Regression and Random Forest
- Deploy predictions on run pages
Who We're Looking For
A master's student in engineering or computer science with a hands-on mindset and interest in aerospace data systems.
Academic Background
- Enrolled in a Master's program in engineering, computer science, data science, or a related field
- Coursework in software development, data management, or scientific computing
- Background in aerospace, fluid dynamics, or materials science is a plus
Technical Skills
- Proficiency in Python and Django
- Experience with data formats and scientific computing libraries (NumPy, pandas, h5py)
- Familiarity with Git and collaborative development workflows
- Basic knowledge of machine learning (scikit-learn or equivalent)
- LaTeX experience is helpful but not required
Soft Skills & Mindset
- Motivated self-starter who can manage a structured multi-week project
- Clear written and verbal communication — deliverables are documented and reviewed
- Comfortable working in a research environment with evolving requirements
- Curiosity about hypersonic testing and thermal protection materials
Apply
Fill out the form below and we'll be in touch. Applications are reviewed on a rolling basis.