AI for Fundamental Physics - Associate Scientist

SLAC

Menlo Park (CA)

On-site

USD 118,000 - 175,000

Full time

14 days+
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Job summary

SLAC National Accelerator Laboratory seeks candidates for the Associate Scientist position in the Fundamental Physics Directorate, focusing on AI and fundamental physics research. The role emphasizes leadership in developing AI-driven techniques and collaborating with Stanford and other centers.

The appointment is a fixed-term, 3–5 years, onsite role with potential for progression based on scientific achievements and program impact.

Qualifications

  • Ph.D. in physics, statistics, computer science, or a related field.
  • At least two years of post-doctoral experience in AI relevant for fundamental physics.
  • Demonstrated knowledge with the standard software tools and computational ecosystems for modern scientific AI.

Responsibilities

  • Develop a world-leading research effort in AI and fundamental physics, as measured by impactful research papers, software, and scientific results.
  • Provide some support / training to the local scientific community.
  • Develop the goals and focus of new and strengthened AI areas at SLAC, centered around lab-wide strategic directions.
  • Grow the base funding in Computational HEP at SLAC to support the candidate's program by the end of the appointment.
  • Mentor postdoctoral researchers and graduate students and provide oversight of engineering and technical staff.

Skills

AI in physics
Fundamental physics
Statistical methods
Computational tools
Science communication

Education

PhD in physics or related field

Tools

Python
ML frameworks
Data analysis

Job description

SLAC National Accelerator Laboratory seeks candidates for the Associate Scientist position in the Fundamental Physics Directorate, focusing on AI and fundamental physics research. The role emphasizes leadership in developing AI-driven techniques and collaborating with Stanford and other centers.

The appointment is a fixed-term, 3–5 years, onsite role with potential for progression based on scientific achievements and program impact.

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