Physics Expert in Statistical Physics for AI Training
Use advanced physics expertise to evaluate and improve AI systems through research-driven work in statistical physics, quantum information, and condensed matter theory. This fully remote contractor role offers flexible part-time hours and $100-$200 per hour.
General Annotation
100% Remote Hourly · $100–$200/hr
$100–$200/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Sep 8, 2026
Posted
Open worldwide
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Opportunities to build a lasting AI training career
Remote work accessible from anywhere worldwide
About AI Training Work
AI training is the human side of building modern artificial intelligence. Experts review, solve, explain, and evaluate challenging material so AI systems can learn to reason more accurately and perform reliably. Specialized contributors bring the subject knowledge that general-purpose models cannot develop on their own.
Work directly on next-generation AI systems
Apply your existing academic or professional expertise
Choose flexible part-time work that fits your schedule
The Physics Expert Role
OpenTrain is seeking a Physics Expert specializing in statistical physics, quantum information, or condensed matter theory for a research-driven project at the intersection of theoretical physics and numerical benchmarking. You will provide high-quality expert input that helps train AI systems to learn, reason, and perform on advanced physics problems.
This is a fully remote, part-time contractor role requiring 5-10+ hours per week. The schedule is flexible, and no prior AI training experience is required.
Pay: $100-$200 per hour
Workload: 5-10+ hours per week
Employment type: Part-time contractor
Work arrangement: Fully remote, worldwide
What You’ll Do
You may participate as a Solver, Auditor, or Adjudicator on assignments aligned with your experience and subfield strengths. Your work will involve both technical problem solving and careful evaluation of solutions, critiques, and numerical results.
Analyze complex statistical physics phenomena involving replicated random-bond Ising and Ashkin-Teller models, the toric-code threshold, and the Nishimori line.
Provide clear, well-documented solutions or 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 challenges involving noncontractible loop defects and related topological features.
Contribute as a Solver, Auditor, or Adjudicator according to your expertise.
Required Qualifications
This role requires an advanced academic background or equivalent practical experience in physics, with a specialization in statistical physics, quantum information, or condensed matter theory. Candidates should have direct research or project experience with the listed theoretical and numerical methods.
PhD or equivalent experience in physics
Specialization in statistical physics, quantum information, or condensed matter theory
Hands-on experience with Kramers-Wannier duality, quenched disorder averaging, and square-lattice self-duality
Proficiency in 4-state Potts model numerical simulations
Experience analyzing domain-wall free energy
Familiarity with topological quantum codes, especially the toric code and its threshold phenomena
Helpful Background
Experience with research and technical communication tools can support success in this role. A publication record demonstrating recent work in relevant research methods is also helpful.
Python
SymPy
Jupyter
LaTeX
Three to five representative publications from the past five years in relevant research methods
Who Should Apply
This opportunity is designed for physicists who want to apply deep theoretical and computational knowledge to the development of AI. It may suit researchers and advanced practitioners with strong expertise in statistical physics, quantum information, or condensed matter theory, even if they have not previously worked in AI training.
Researchers with advanced theoretical physics expertise
Physicists experienced in statistical models, topological codes, or numerical benchmarking
Experts who can explain complex technical reasoning clearly
Candidates seeking flexible, high-value remote project work
How to Get Started
Create a free OpenTrain account, build your profile around your physics expertise, and apply to this project. If selected for relevant assignments, you will contribute as a Solver, Auditor, or Adjudicator based on your qualifications and subfield strengths.
Create or update your free OpenTrain profile
Highlight relevant research, simulations, publications, and technical tools
Apply in minutes for consideration
Set aside 5-10+ flexible hours per week if selected
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