Postdoctoral Appointee - Data Analysis for Large-scale Gamma-ray Spectrometers
ID: 7100067 (Ref.No. 413341)
Posted: May 13, 2022
Application Deadline: Open Until Filled
Argonne National Laboratory seeks a postdoctoral appointee to conduct research in data analysis for large-scale Gamma-ray spectrometers. The successful candidate will be hired in the Mathematics and Computer Science Division and will work closely with scientists in the Low-Energy Nuclear Physics Research Group (LER) of the Physics Division. The detection of gamma-ray emission from excited nuclear states plays a vital role in nuclear science. The goal of this multi-disciplinary project is to attack two open and connected problems in the utilization of large gamma-ray arrays, namely (1) to make significant improvements in Gamma-ray tracking as it applies to GRETINA/GRETA, and (2) to develop a new framework for the construction of nuclear level schemes which are the major end products of these world-class spectrometers. We aim to leverage advances in machine-learning, high-performance computing, and physics insight to achieve this goal.
This project brings together two world-leading divisions, Mathematics and Computer Science, see https://www.anl.gov/mcs and Physics, see https://www.anl.gov/phy. As a leader in the computing sciences, the MCS Division provides the numerical tools and technology for solving some of our nation’s most critical scientific problems. The Argonne Physics Division has programs in low energy and medium energy nuclear physics, nuclear theory, nuclear data, accelerator R&D and operates the DOE Office of Science, Office of Nuclear Physics National User Facility, the Argonne Tandem-Linac Accelerator System (ATLAS). In addition to our world-class research, we develop the software for some of the fastest, most powerful computer systems in the world: systems that are enabling scientists to tackle problems previously considered infeasible.
- Recently received or near completion of their Ph.D. in physics, applied mathematics, computer science, or related discipline within the last 3 years.
- Graduate/postgraduate research in machine learning, and programming experience (Python, PyTorch, C/C++, or Fortran).
- In addition, experience in one or more of the following: design of nuclear physics experiments and physics interpretations, data analysis, and mathematical optimization.
Job FamilyPostdoctoral Family
Job ProfilePostdoctoral Appointee
Worker TypeLong-Term (Fixed Term)
Time TypeFull time
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