** (posted 2020/11/02)| Position ID: | Stanford University / SLAC National Accelerator Laboratory-FUNDAMENTAL PHYSICS DIRECTORATE-ASSOCSSFPD [#17426] |
| Position Title: | Associate Staff Scientist FPD |
| Position Type: | Tenured/Tenure-track faculty |
| Position Location: | Menlo Park, California 94025, United States [map] |
| Subject Area: | High Energy Physics |
| Appl Deadline: | 2020/12/15 11:59PM** (posted 2020/11/02) |
| Position Description: |
The Fundamental Physics Directorate (FPD) at the SLAC National Accelerator Laboratory (SLAC) is seeking a machine learning (ML) scientist to apply for a career-track position at the Associate Staff Scientist level. Exceptional candidates may be considered for a more senior position, commensurate with qualifications. This position offers exciting opportunities across the spectrum of science programs in FPD. The Directorateâs scientists are involved in a broad range of projects at the at the Cosmic Frontier and the Energy and Intensity Frontiers of High Energy Physics. Recent ML applications include those listed in https://ml.slac.stanford.edu. The position is not specific to a particular project, but is targeting the development and application of Machine Learning methods applicable for science across the FPD. This ML scientist will develop a research agenda in applications of Machine Learning in High Energy Physics, will be strongly encouraged to collaborate on projects with groups across the FPD, and, where possible, will help to develop methodological connections between groups. The expected start time for this position is early 2021. Qualifications: â¨These are highly competitive positions as part of the research program at SLAC, requiring a background of demonstrated excellence in machine learning applications. Candidates should hold a Ph. D. in Computer Science, Machine Learning, Statistics, or related field, or hold a Ph. D. in Physics with demonstrated experience in Machine Learning. Candidates holding a Masters degree in Computer Science, Machine Learning, Statistics, Physics, or related field, and having demonstrated several years experience in Machine Learning research and application may also be considered. Experience in scientific applications of Machine Learning is highly beneficial, especially in particle physics, dark matter physics, and / or cosmology. How to Apply: Submit
the following items online at this website to complete your application:
Applications must be received by December 15, 2020 to ensure full consideration. Questions should be directed to the Chair of the Search Committee, Dr. Charles Young (young@slac.stanford.edu). SLAC National Accelerator Laboratory is an Affirmative Action / Equal Opportunity Employer and supports diversity in the workplace. All employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, marital or family status, sexual orientation, gender identity, or genetic information. All staff at SLAC National Accelerator Laboratory must be able to demonstrate the legal right to work in the United States. SLAC is an E-Verify employer. |
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