Physicist for AI Training, Statistical Physics / Quantum Information / Conden...

Role Overview

Apply advanced theoretical physics expertise to a research-driven project that helps train next-generation AI systems through rigorous analysis, numerical benchmarking, and well-documented technical input. This remote contractor role focuses on statistical physics, quantum information, and condensed matter topics. Prior AI experience is not required.

Key Responsibilities

• Analyze complex statistical physics phenomena, including replicated random-bond Ising and Ashkin-Teller models, the toric-code threshold, and the Nishimori line.
• Produce clear, well-documented solutions or critiques involving Kramers-Wannier duality, quenched disorder averaging, square-lattice self-duality, and domain-wall free energy.
• Conduct and interpret advanced numerical work related to 4-state Potts model simulations.
• Identify, discuss, and resolve technical challenges involving noncontractible loop defects and related topological features.
• Contribute to assignments as a Solver, Auditor, or Adjudicator based on your experience and subfield strengths.

Qualifications

• Advanced academic background in physics, including a PhD or equivalent experience, with specialization in statistical physics, quantum information, or condensed matter theory.
• Hands-on research or project experience with Kramers-Wannier duality, quenched disorder averaging, and square-lattice self-duality.
• Demonstrated proficiency in 4-state Potts model numerical simulations and domain-wall free energy analysis.
• Familiarity with topological quantum codes, particularly the toric code and its threshold phenomena.

Work Terms

• Remote, independent contractor engagement.

Compensation

• $80 to $160 per hour.