Stanford University / SLAC National Accelerator Laboratory
Position ID:
Position Title:
Associate Scientist - Machine Learning
Position Type:
Other
Position Location:
Menlo Park, California 94025, United States of America
Subject Area:
Appl Deadline:
2024/05/31 11:59PM
finished (2023/12/12, finished 2024/10/03, listed until 2024/06/12)
finished (2023/12/12, finished 2024/10/03, listed until 2024/06/12)Position Description:
*** this position has been closed and new applications are no longer accepted. ***
SLAC National Accelerator Laboratory seeks a research scientist with a proven track record of recognized scientific achievement in applying machine learning (ML) to the physical sciences. SLAC is one of the world’s premier research laboratories, with internationally leading capabilities in photon science, accelerator physics, high energy physics (HEP), and energy sciences.
Machine learning is expected to play an important role in nearly every major project at SLAC. Applications include deep learning for detector analysis, online control of facilities, surrogate models for high-fidelity simulations, and new modes of data analysis to handle data rates that can reach TBs/second.
The ML department’s goal is to support discovery across SLAC’s science mission. Though the position is not oriented towards foundational computer science, the candidate should be comfortable enough with ML to extend the limits of current algorithms. Likewise researchers should have sufficient science background to be an integral member of domain science teams. The role is interdisciplinary and collaborative, and the candidate will work jointly with scientists and engineers at SLAC, academics at Stanford, industrial partners in Silicon Valley, and facility users from around the world. Finally, the candidate should have a creative spark to tackle unsolved problems in science.
The applicant can expect to work projects across the range of science domains at SLAC. For this position, there will be an emphasis on differentiable simulations, inverse problems, and experimental design. Research experience in these areas will be considered a plus.
Given the nature of this position, SLAC is open to on-site and hybrid work options.
Your Specific Responsibilities Include
- Work with multiple domain science teams to apply ML to the highest-impact problems at SLAC.
- Develop and lead new research programs applying ML to science, with impact on the Department of Energy’s wide range of science.
- Develop and lead proposals for new funding opportunities to expand ML activities at SLAC
- Support machine learning broadly across the lab, including education and support of domain scientists.
Applicants must provide evidence of either a recently completed PhD degree or confirmation of completion of the PhD degree requirements prior to starting the position. Applicants should also include a cover letter, a statement of research area including brief summary of accomplishments, a curriculum vitae, a list of publications, and names of three references for future letters of recommendation with the application.
We are looking for candidates, with the following minimum criteria in mind:
- Ph.D. in Computer Science, Physics, Chemistry, Computational Biology, or related field.
- Three years of post-graduate research applying machine learning to the physical sciences.
- Strong background in physical sciences, ideally at the graduate level, and strong interest in fundamental research in the physical sciences.
- Strong background in machine learning and experience in collaborative software projects.
- Strong research/publication record commensurate with level of work experience.
- Experience developing and delivering research activities, including progress reports and presentations to diverse stakeholders.
- Experience in writing proposals to fund scientific research.
- Excellent verbal and written communication skills and the ability to convey complex technical concepts.
- Ability to work and communicate effectively with a diverse population.
- Ability to collaborate across organizations and manage/lead cross-functional efforts.
- Experience (3+ years) in high-energy physics, photon science, materials science, and accelerator physics.
- Experience (3+ years) in deep learning, active learning, differentiable simulations, and inverse problems.
The expected pay range
for this position is $115,000 to $171,000 per annum. SLAC National
Accelerator Laboratory/Stanford University provides pay ranges
representing its good faith estimate of what the university reasonably
expects to pay for a position. The pay offered to a selected candidate
will be determined based on factors such as (but not limited to) the
scope and responsibilities of the position, the qualifications of the
selected candidate, departmental budget availability, internal equity,
geographic location and external market pay for comparable jobs.
If interested, please apply at this link: https://www.linkedin.com/jobs/view/3754649386/?alternateChannel=search&;refId=q%2BaDfInkBZtIX3sWh6waoQ%3D%3D&trackingId=9iDd8fIw00NnY0%2FH%2BezuVw%3D%3D
Application Materials Required:
Submit the following items online at this website to complete your application:
- Cover letter
- Curriculum Vitae
- Research statement
- Publication list
- Three reference letters (to be submitted online by the reference writers on this site )
And anything else requested in the position description.
Further Info: