Physicist (PhD), Atomic, Molecular & Optical Physics

You will help assess and improve AI systems that handle specialized physics topics. The work combines expert analysis, technical critique, and clear scientific communication.

You will review research methods, evaluate technical reasoning, and explain complex physics in structured written and verbal formats. Examples must come from research or projects that can be legally shared.

• Review ab initio configuration interaction methods for calculating polarizability in atomic systems.
• Analyze and critique atomic-structure calculations involving the Yb-171 and Yb-174 isotopes.
• Identify and explain sigma and pi transitions in relevant atomic spectra.
• Evaluate technical reasoning using physical principles and provide clear, concrete examples.

What it pays and takes

This is a part-time contract role for a physics specialist.

• Pay: $100 to $200 per hour.
• Time: Less than 20 hours per week.
• Language: Fluent in English.
• Education: An advanced degree in Physics, or equivalent experience, focused on AMO physics or optical properties of materials.
• Experience: Proven experience with ab initio quantum chemistry calculations and configuration interaction approaches to polarizability.
• Technical knowledge: Atomic-structure computation techniques for ytterbium isotopes, especially Yb-171 and Yb-174, plus the ability to distinguish sigma and pi transitions in atomic contexts.
• Communication: Clear, structured scientific communication in writing and speech.
• Location: remote, open to applicants in the United States.

How it works

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.

About AI training work

AI training is the human work behind systems that learn from examples, including reviewing model responses and judging whether technical reasoning is accurate. People with specialized knowledge help make these systems more reliable in fields where general feedback is not enough.