Theoretical Physicist AI Training

Apply advanced theoretical physics and numerical analysis expertise to help improve next-generation AI systems through rigorous, research-driven problem solving and evaluation. This remote contract opportunity focuses on statistical physics, quantum information, and condensed matter topics. Prior AI experience is not required.

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

• 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 with 4‑state Potts model numerical simulations and domain‑wall free‑energy analysis.
• Familiarity with topological quantum codes, particularly the toric code and threshold phenomena.

Remote contract engagement.

$80 to $160 per hour.