Physicist (PhD), Statistical Physics, Quantum Information & Condensed Matter

You will provide expert analysis and feedback for a research-driven AI training project focused on theoretical physics and numerical benchmarking. No prior AI training experience is required.

Assignments may involve solving, reviewing, or adjudicating technical work based on your research background and subfield strengths.

• Analyze replicated random-bond Ising and Ashkin-Teller models, the toric-code threshold, and the Nishimori line.
• Write clear, well-documented solutions or critiques involving Kramers-Wannier duality, quenched disorder averaging, square-lattice self-duality, and domain-wall free energy.
• Run and interpret numerical simulations involving the 4-state Potts model.
• Investigate technical questions involving noncontractible loop defects and related topological features.
• Contribute as a Solver, Auditor, or Adjudicator on assigned projects.

This is a part-time, fully remote contractor role with a flexible schedule. The work requires advanced subject knowledge and direct research or project experience in the listed methods.

• Pay: $100 to $200 per hour.
• Schedule: 5 to 10 or more hours per week.
• Location: remote, open to applicants in the United States.
• Language: Fluent in English.
• Education: PhD or equivalent experience in physics, specializing in statistical physics, quantum information, or condensed matter theory.
• Experience: Hands-on use of Kramers-Wannier duality, quenched disorder averaging, and square-lattice self-duality.
• Technical background: Numerical simulation and analysis using the 4-state Potts model and domain-wall free energy.
• Subject knowledge: Topological quantum codes, especially the toric code and its threshold phenomena.
• Helpful tools: Python, SymPy, Jupyter, and LaTeX.
• Helpful background: A strong publication record with 3 to 5 relevant publications from the past 5 years.

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

AI training is the human work behind systems that learn from examples, expert answers, and ratings. People with advanced subject knowledge help evaluate and improve how models reason, making specialist expertise valuable in projects like this one.