Quantum Physics Exact-Diagonalization Research Specialist
Apply advanced condensed matter and quantum information expertise to evaluate AI systems through exact diagonalization, symmetry methods, and quantum many-body benchmark analysis. Remote, part-time contract at $80–$160 per hour.
Coding & Software
100% Remote Hourly · $80–$160/hr
$80–$160/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Aug 2, 2026
Posted
Open worldwide
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AI training is the human side of developing modern artificial intelligence. Experts create, solve, review, and evaluate examples that help AI systems become more accurate and capable. In this role, your physics expertise will support research-level benchmark analysis and model feedback.
The Role
OpenTrain is seeking a Condensed Matter and Quantum Information Physics Expert for a research-level physics benchmark focused on the PXP model, Rydberg blockade, quantum many-body scars, and constrained quantum dynamics.
Depending on your methods expertise and subfield alignment, your contributions may involve solver, auditor, or adjudicator work. You will combine computational physics, mathematical reasoning, numerical analysis, and careful written evaluation to help assess and improve AI systems.
Remote contractor engagement
Approximately 10 hours per week
Expected project duration of 8–10 weeks
Compensation of $80–$160 per hour
English-language project
What You'll Do
You will develop and analyze exact-diagonalization implementations for complex quantum systems, working with symmetry-reduced representations and large Hilbert-space subspaces. The work includes both technical analysis and detailed written communication for physics benchmark evaluation.
Develop and analyze exact-diagonalization implementations using translation and reflection symmetries
Work with QuSpin and system sizes of at least L = 26 where appropriate
Construct and manipulate block-diagonalized subspaces
Improve computational efficiency and numerical fidelity across large Hilbert spaces
Evaluate overlaps with Z2 states and interpret the resulting physical insights
Produce detailed written feedback, analytic reports, and benchmark assessments
Required Expertise
This role requires advanced academic training or equivalent practical experience in condensed matter physics, quantum information, or a closely related discipline. The structured listing identifies the opportunity as entry level, but the technical scope calls for demonstrated expertise in the methods and physical concepts below.
Exact diagonalization using translation and reflection symmetries, preferably with QuSpin
Hamiltonian block-diagonalization and efficient work with large Hilbert-space subspaces
Strong understanding of quantum many-body scars, Rydberg blockade, and constrained dynamics
Experience analyzing overlaps with Z2 or related quantum states
Ability to interpret numerical results and connect them to physical insights
Advanced academic or equivalent practical background in condensed matter physics or quantum information
Helpful Technical Background
Experience with the following tools can support the computational, analytical, and reporting aspects of the project. Prior AI training experience is not required; the focus is on applying rigorous physics expertise to benchmark analysis and model feedback.
Python
QuSpin
SymPy
Jupyter
LaTeX
Why This Work Matters
AI systems learn from carefully prepared and reviewed examples, including technically demanding problems and expert evaluations. By solving and auditing advanced quantum physics tasks, you can contribute directly to how cutting-edge models reason about specialized scientific material.
AI training and data-labeling work is a growing way to work in tech remotely and flexibly. OpenTrain helps contributors build a lasting record of this work, discover projects aligned with their expertise, and develop an AI training career.
How to Get Started
Create a free OpenTrain account, build your profile around your condensed matter or quantum information background, and apply to this contract opportunity. Highlight your exact-diagonalization, symmetry-methods, computational physics, and quantum many-body experience.
Showcase relevant academic or practical physics experience
Describe work with exact diagonalization and Hamiltonian symmetries
Include experience with QuSpin or comparable computational methods
Explain your familiarity with quantum many-body scars, Rydberg blockade, and constrained dynamics
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