Physics Expert – Statistical Physics & Quantum Information

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role and the #1 platform for finding and building careers in AI training and data labeling. We connect experts with projects where human knowledge helps shape how advanced AI systems reason, communicate, and solve problems.

Creating an OpenTrain account is free, and no prior AI experience is required for this opportunity. Your physics expertise is the key qualification.

About AI Training Work

AI training is the human side of building artificial intelligence. Experts prepare examples, assess model responses, identify errors, and provide rigorous feedback so AI systems can improve their performance on specialized tasks.

This project focuses on evaluating technical reasoning in theoretical and computational physics. Your work will contribute to next-generation AI systems while giving you the opportunity to apply advanced subject-matter knowledge remotely.

The Role

OpenTrain AI is seeking experienced Physics Experts specializing in Statistical Physics, Quantum Information, or Condensed Matter Theory for a research-driven project at the intersection of theoretical physics and numerical benchmarking.

As a contractor, you will analyze complex physics problems, evaluate technical solutions, and provide clear, high-quality expert insights. Depending on your expertise and subfield specialization, you may participate as a Solver, Auditor, or Adjudicator on project assignments.

The project is remote and open worldwide. The expected project duration is 3 to 6 months, and fluent English proficiency is required.

• Employment type: Contractor
• Location: Remote, worldwide
• Compensation: $80–$160 per hour
• Expected duration: 3–6 months
• Experience level: Expert

What You'll Do

You will work on challenging theoretical and computational physics problems where rigorous reasoning, numerical analysis, and deep subject-matter expertise are essential. Assignments may involve text-based question answering, evaluation and rating, and technical response generation.

• Analyze replicated random-bond Ising and Ashkin–Teller models, toric-code thresholds, and the Nishimori line.
• Develop and assess solutions involving Kramers–Wannier duality, quenched disorder averaging, and square-lattice self-duality.
• Analyze domain-wall free energy and technical challenges involving noncontractible loop defects and related topological features.
• Conduct and interpret advanced numerical simulations, particularly involving the 4-state Potts model.
• Provide clear, well-documented solutions and technical critiques.
• Serve as a Solver, Auditor, or Adjudicator based on your expertise and specialization.
• Help evaluate and improve the ability of advanced AI systems to reason about complex scientific concepts.

Required Expertise

This opportunity is designed for professionals with research-level knowledge in relevant areas of physics. No prior AI experience is required, but strong analytical, mathematical, numerical, and technical communication skills are essential.

• Advanced expertise in Physics
• Knowledge of Kramers–Wannier duality
• Experience with quenched disorder averaging
• Understanding of square-lattice self-duality
• Experience analyzing domain-wall free energy
• Experience with 4-state Potts model numerical simulations
• Familiarity with noncontractible loop defects and related topological features
• Familiarity with topological quantum codes, particularly the toric code and its threshold phenomena
• Fluent English proficiency

Preferred Qualifications

A PhD or equivalent advanced experience in Physics is preferred, particularly with specialization in Statistical Physics, Quantum Information, or Condensed Matter Theory. Hands-on research or project experience in the listed areas will help you contribute effectively to complex assignments.

• Research or project experience with Kramers–Wannier duality, quenched disorder averaging, and square-lattice self-duality
• Demonstrated experience with 4-state Potts model numerical simulations
• Experience with domain-wall free-energy analysis
• Strong analytical, mathematical, numerical, and technical communication abilities

Why Join This Project

AI training and data labeling are growing fields in which specialists help shape the behavior of modern AI systems. By applying your knowledge of theoretical and computational physics, you will work at the cutting edge of scientific reasoning and AI development.

The role is fully remote and offers expert-level contractor compensation. It is suited to physics researchers and specialists who enjoy solving difficult problems and communicating rigorous technical judgments.

• Apply your existing physics expertise without prior AI experience
• Work remotely from anywhere in the world
• Contribute to the evaluation of advanced AI reasoning
• Engage with challenging statistical physics and quantum information problems