Physicist for AI Model Training (Statistical Physics / Quantum Information / ...

Apply deep theoretical and numerical physics expertise to analyze and resolve advanced problems in statistical physics, quantum information, and condensed matter. Work on research-driven benchmarking and problem-solving that will be used to train and evaluate next-generation AI systems. No prior experience in AI is required, domain knowledge is the primary qualification.

• Analyze and provide expert insight into replicated random-bond Ising and Ashkin-Teller models, including phenomena along the Nishimori line.
• Study and apply toric-code threshold theory and related topological quantum code concepts.
• Deliver clear, well-documented solutions or critiques on problems involving Kramers-Wannier duality, quenched disorder averaging, and square-lattice self-duality.
• Perform and interpret advanced numerical work focused on the 4-state Potts model, including analysis of domain-wall free energy.
• Identify, discuss, and resolve technical challenges related to noncontractible loop defects and other topological features.
• Contribute on specific assignments in one of the following roles based on experience, Solver, Auditor, or Adjudicator.

• Advanced academic background, PhD or equivalent experience, in physics with specialization in statistical physics, quantum information, or condensed matter theory.
• Direct, hands-on experience applying Kramers-Wannier duality, quenched disorder averaging, and square-lattice self-duality in research or project settings.
• Demonstrated proficiency with numerical simulations involving the 4-state Potts model and analysis of domain-wall free energy.
• Familiarity with topological quantum codes, especially the toric code, and threshold phenomena.
• No prior AI experience required, candidates are selected for domain expertise.

• Engagement type, independent contractor.
• Location, remote.
• Assignments are research-driven, at the intersection of theoretical physics and numerical benchmarking, and will be assigned according to experience and subfield strengths.

Hourly rate, $80 - $160 per hour.

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