Physics Research Review Expert

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. It helps specialists discover meaningful projects, build a professional profile, and apply their expertise to the development of emerging AI systems.

About AI Training Work

AI training is the human side of building artificial intelligence. Experts review examples and model outputs, identify errors, and provide feedback that helps AI systems produce more accurate, reliable, and useful results.

In this project, your physics expertise will help evaluate scientific reasoning used in AI training. Your feedback can improve how models handle derivations, theoretical arguments, assumptions, and technical explanations.

• Remote work that can fit around research, teaching, or other commitments
• Flexible part-time work with less than 20 hours per week
• Opportunity to apply advanced physics knowledge to cutting-edge AI development

The Role

OpenTrain is seeking a Physics Research Review Expert to evaluate physics solutions, mathematical derivations, and theoretical arguments. You will determine whether reasoning is correct and sufficiently justified, distinguish substantive scientific problems from cosmetic issues, and provide technically rigorous feedback on researcher- and AI-generated material.

This is an entry-level project classification, but the role requires PhD-level physics expertise and an active record of independent research in a specialized subfield.

• Contractor, part-time position
• Worldwide opportunity
• English-language work
• Pay range: $80–$150 USD per hour

What You’ll Do

You will critically assess scientific reasoning and explain your conclusions in structured written feedback. The goal is to identify what is correct, clarify what needs improvement, and provide actionable guidance for iterative improvement.

• Review physics solutions, derivations, and theoretical arguments for correctness and methodological soundness
• Identify errors, unjustified transitions, missing assumptions, dimensional inconsistencies, and weaknesses in logic
• Distinguish substantive scientific flaws from stylistic or cosmetic issues
• Explain the reasoning behind identified problems with technical precision
• Recognize valid reasoning that could be sharpened, clarified, or made more efficient
• Use LaTeX, SymPy, Python, and Jupyter to independently verify or counter-check scientific claims as appropriate
• Evaluate researcher- and AI-generated scientific material
• Deliver nuanced, constructive, structured feedback

Required Qualifications

You must have advanced physics expertise, strong technical judgment, and the ability to communicate complex feedback clearly. Experience evaluating other physicists’ work is especially relevant.

• PhD in physics
• Active independent research in a specialized physics subfield
• Advanced proficiency with LaTeX, SymPy, Python, and Jupyter for theoretical modeling and computational validation
• Ability to detect subtle errors, missing assumptions, dimensional inconsistencies, and methodological flaws
• Experience evaluating physics work through peer review, supervision, dissertation committees, group seminars, or journal clubs
• Exceptional written communication and the ability to provide nuanced, constructive feedback with technical rigor
• Reliable high-speed internet
• A computer suitable for demanding technical work

Relevant Research Background

Researchers from a range of specialized areas may be well suited to this work. Postdoctoral research, research fellowships, junior or assistant professorships, senior research scientist experience, and recent representative publications are particularly relevant.

• High-energy physics
• Mathematical physics
• Condensed matter
• Atomic, molecular, and optical physics
• Quantum optics
• Statistical physics
• Biophysics
• Gravitation and cosmology
• Quantum information
• Optical materials

Work With OpenTrain

OpenTrain connects skilled specialists with meaningful AI training projects that benefit from their expertise. By contributing your physics judgment, you can build experience at the intersection of professional research and emerging AI systems while working on a flexible schedule.

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