Automated Feature Discovery & Anomaly Detection for Scientific Data Archives

PPPL summer internship program participant.

A U.S. Department of Energy National Laboratory managed by Princeton University, the Princeton Plasma Physics Laboratory (PPPL) is tackling the world’s toughest science and technology challenges using plasma, the fourth state of matter. With more than 70 years of history, PPPL is a leader in the science and engineering behind the development of fusion energy, a potentially limitless energy source. PPPL is also using its expertise to advance research in the areas of microelectronics, quantum sensors and devices, and sustainability sciences. Whether it be through science, engineering, technology or professional services, every team member has an opportunity to contribute to our mission and vision. Come join us!

Core Duties: 

• This project focuses on Unsupervised Representation Learning to automate data curation for the SURGE framework. The intern will build a pipeline using Autoencoders to extract meaningful features from high-dimensional scientific data, creating a "Latent Atlas" that autonomously tags physics regimes and identifies outliers. The work will involve training deep learning models to compress raw data into structured feature spaces required for downstream surrogate modeling.

Education and Experience: 

• Undergraduate student.

Knowledge, Skills and Abilities: 

• This project is suitable for a student with a strong interest in Deep Learning (Autoencoders/Unsupervised Learning) and Data Mining. They will be working on the "Feature Extraction" component of the SURGE ecosystem.

Working Conditions: 

• On-site. 

Princeton University is an Equal Opportunity and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.

The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.

If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.

The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.

Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from participation in certain foreign government talent recruitment programs. All PPPL employees are required to disclose any participation in a foreign government talent recruitment program and may be required to withdraw from such programs to remain employed under the DOE Contract.