LLNL-MI-822468
Want to help develop a new technology to better understand nuclear accidents, prevent nuclear smuggling, and make the world a safer place?
The Nuclear Science and Security Consortium at the University of California, Berkeley welcomes applications for an undergraduate research assistant in neutron spectrum unfolding algorithms. The student will use artificial neural networks to deconvolute the measurements from a neutron detector. The responsibilities of this position will include writing software in Python, constructing neural networks in TensorFlow, Monte Carlo transport modeling using MCNP6, and attending a weekly group meeting to discuss progress. This assistantship provides potential opportunities for authorship of peer-reviewed journal articles. Successful candidates will have a passion for science and an interest in experimental nuclear physics.
Conceptualization of unfolding process with neural networks.
Required:
- Undergraduate degree in progress at UC Berkeley
- Experience working within an interdisciplinary team
- U.S. Citizen
Highly Preferred:
- Junior or senior-level standing
- Familiarity with Python, neural networks, TensorFlow
- Familiarity with Monte Carlo transport codes, like MCNP
- Coursework/experience with nuclear or radiation physics
Undergraduates The position is at $20 per hour, 40 hours per week, during a Summer 2021 remote internship.
To apply, submit a cover letter and CV to
Charlotte Carr (nssc_info@berkeley.edu) Nuclear Science and Security Consortium
Please put “UNDERGRADUATE SUMMER RESEARCH IN MACHINE LEARNING APPLIED TO NEUTRON SPECTRUM UNFOLDING” in the subject line of your email. Deadline to apply 6/1/2021.
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