The Complexity Science research team in the Department of Nuclear Engineering at the University of California, Berkeley welcomes applications for an undergraduate research assistant in machine learning and algorithm development. The goal of this work is to develop and apply transferable multisource machine learning methods to classify nuclear operations—such as reactor operational states, fuel delivery, and reactor refueling—at previously unseen nuclear facilities of interest. Working within a team of nuclear engineers and computer scientists, the candidate will primarily contribute through software development and data analysis. Additional tasks may include supporting experimental data collection campaigns at nuclear reactor facilities.
Appointment:
This remote position is available immediately. Hours are flexible, with up to 40 hours per week (summer) and ~10 hours per week (academic year). Pay rate is $20 per hour.
Required:
- Undergraduate degree in progress at UC Berkeley in EECS, Nuclear Engineering, Physics, Math/Stats, Data Science, or related disciplines
- Proficient in Python
- Highly motivated team player
- Independent and creative thinker
Desired:
- Experience with Keras/TensorFlow or other ML platforms
- Familiarity with a Linux/Unix environment
To apply:
Send a cover letter and CV to Dr. Bethany Goldblum at bethany@nuc.berkeley.edu with “Complexity Science Undergrad” in the subject line
JUL