Research Associate - Theoretical (Particle Physics)
Apply NowCompany: SLAC National Accelerator Laboratory
Location: Menlo Park, CA 94025
Description:
SLAC Job Postings
Position Overview:
The SLAC FPD Theory group plans to appoint a postdoctoral Research Associate (RA) for a 1.5-year term, beginning October 1, 2025 or earlier, at the interface of machine learning and quantum field theory. The successful applicant will join a project with Lance Dixon, Kyle Cranmer, and other collaborators at the University of Wisconsin, the Niels Bohr Institute, and elsewhere, which will apply cutting-edge machine learning methods to deciphering the analytic structure of scattering amplitudes in quantum chromodynamics and a related theory, planar N=4 super-Yang-Mills theory.
The senior members of the SLAC FPD theory group are: Lance Dixon, Alexander Friedland, Rebecca Leane, Bernhard Mistlberger, Michael Peskin, Thomas Rizzo, Philip Schuster and Natalia Toro.
The group's broader interests cover quantum field theory, particle theory, and the interface of particle physics and astroparticle physics. There are a variety of other machine learning and AI efforts at SLAC and Stanford, including Stanford Data Science. Applications should include a CV, a statement of research interests, a publication list, and the names of three senior physicists or computer/data scientists who will provide letters of recommendation. SLAC is an affirmative action, equal opportunity employer.
Applications should be received before April 30, 2025 for full consideration. https://theory.slac.stanford.edu/
Your specific responsibilities include:
SLAC Employee competencies:
Classification Title: Research Associate -Theoretical
Duration: Fixed Term
Grade: G, Job code: 0126
The expected pay range for this position is $70,000 to $100,000 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.
Position Overview:
The SLAC FPD Theory group plans to appoint a postdoctoral Research Associate (RA) for a 1.5-year term, beginning October 1, 2025 or earlier, at the interface of machine learning and quantum field theory. The successful applicant will join a project with Lance Dixon, Kyle Cranmer, and other collaborators at the University of Wisconsin, the Niels Bohr Institute, and elsewhere, which will apply cutting-edge machine learning methods to deciphering the analytic structure of scattering amplitudes in quantum chromodynamics and a related theory, planar N=4 super-Yang-Mills theory.
The senior members of the SLAC FPD theory group are: Lance Dixon, Alexander Friedland, Rebecca Leane, Bernhard Mistlberger, Michael Peskin, Thomas Rizzo, Philip Schuster and Natalia Toro.
The group's broader interests cover quantum field theory, particle theory, and the interface of particle physics and astroparticle physics. There are a variety of other machine learning and AI efforts at SLAC and Stanford, including Stanford Data Science. Applications should include a CV, a statement of research interests, a publication list, and the names of three senior physicists or computer/data scientists who will provide letters of recommendation. SLAC is an affirmative action, equal opportunity employer.
Applications should be received before April 30, 2025 for full consideration. https://theory.slac.stanford.edu/
Your specific responsibilities include:
- Conduct research in theoretical particle physics and machine learning.
- Participate in and contribute to general group activities
- Present your research results at seminars, scientific conferences and workshops.
- PhD in Particle Physics or Computer Science, or a closely related field with demonstrated coursework and research experience in either area
- Demonstrated research experience as evidenced by a publication record.
- A solid foundation and research background in Particle Physics and/or Machine Learning.
- Ability to carry out independent research.
- Strong analytical and computational skills.
- Experience in training AI models.
SLAC Employee competencies:
- Effective Decisions: Uses job knowledge and solid judgment to make quality decisions in a timely manner.
- Self-Development: Pursues a variety of venues and opportunities to continue learning and developing.
- Dependability: Can be counted on to deliver results with a sense of personal responsibility for expected outcomes.
- Initiative: Pursues work and interactions proactively with optimism, positive energy, and motivation to move things forward.
- Adaptability: Flexes as needed when change occurs, maintains an open outlook while adjusting and accommodating changes.
- Communication: Ensures effective information flow to various audiences and creates and delivers clear, appropriate written, spoken, presented messages.
- Relationships: Builds relationships to foster trust, team collaboration, and a positive climate to achieve common goals.
- Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
- Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
- Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for environment, safety and security; communicates related concerns; uses and promotes safe behaviors based on training and lessons learned. Meets the applicable roles and responsibilities as described in the ESH Manual, Chapter 1General Policy and Responsibilities: http://www-group.slac.stanford.edu/esh/eshmanual/pdfs/ESHch01.pdf
- Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, http://adminguide.stanford.edu.
Classification Title: Research Associate -Theoretical
Duration: Fixed Term
Grade: G, Job code: 0126
The expected pay range for this position is $70,000 to $100,000 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.