Physics Expert (Postdoc / Junior professor)

$80–150/hrrate as listed

micro1 is contracting physics PhDs to review AI-generated derivations, solutions, and theoretical arguments in their subfield, flagging errors, unstated assumptions, and dimensional inconsistencies. Work is remote and contract-based, with observed rates of $80–150/hr depending on subfield and depth of review.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

The work

You receive physics problems together with candidate solutions — most produced by AI models, some by other researchers — and you adjudicate them. That means following a derivation line by line, checking dimensional consistency and limiting cases, identifying where a step is asserted rather than justified, and deciding whether an argument fails because of a genuine physical error or merely reads awkwardly. Your written feedback has to be specific enough that someone else could act on it: which equation, which assumption, what the correct treatment would be. When reasoning is already sound, you're often asked to note where it could be tightened.

Much of the verification is hands-on. Expect to use SymPy or Python in a Jupyter notebook to check an integral, reproduce a numerical result, or construct a counterexample, and LaTeX to write up what you find. No AI or machine learning background is expected — micro1 states plainly that domain knowledge is what matters here.

What the screen looks for

Verified research identity. A physics PhD plus recent publications in a named subfield — high energy or mathematical physics, condensed matter, AMO and quantum optics, biophysics and statistical physics, gravitation and cosmology, quantum information, optical materials. Have arXiv or DOI links ready.
Depth under follow-up. The interview will push past your abstract into method choices, approximations you made, and what you'd do differently. Surface-level familiarity with your own papers shows quickly.
Reviewer judgment. Prior referee work, dissertation committees, or group-seminar critique matter because the core skill is separating substantive scientific defects from cosmetic ones.
Written precision. Feedback quality is the deliverable; vague or hedged criticism is the most common failure mode.

Logistics

Remote contractor engagement, focused on US, Canada, and UK time zones. Work is asynchronous and batch-based — tasks arrive in volume and you complete them on your own schedule, which makes it workable alongside a postdoc or teaching load. Volume fluctuates with client demand, so treat this as variable supplemental work rather than a predictable weekly commitment. You'll need reliable high-speed internet and a machine capable of running computational notebooks comfortably.

What they look for

Physics Mastery
Written Technical Communication
Critical Evaluation & Error Detection
Calibrated Technical Judgment
Verification & Cross-Checking Fluency

Before you apply

Would you pass this screen?

Drawn from what this listing actually requires. Answered in your browser — nothing is sent to us, and we do not store your answers.

Do you hold a PhD in physics or a closely related field (e.g., mathematical physics, biophysics, or physics-adjacent discipline where your dissertation was in physics)?
PhD in Physics · required
Do you have at least one peer-reviewed publication or accepted preprint in a physics subfield within the last five years, with an arXiv identifier or DOI you can provide?
Active research record (last 5 years) · required
Are you currently or have you recently been (within the last 3 years) employed as a postdoctoral researcher, research fellow, junior/assistant professor, or senior research scientist in physics?
Postdoc or faculty position (current or recent) · preferred
Do you have hands-on experience using LaTeX for technical writing and Python (including SymPy and Jupyter) for scientific computation or verification within the last two years?
Proficiency with LaTeX and Python · preferred
Do you have reliable access to high-speed internet (≥25 Mbps) and a computer capable of running Jupyter, SymPy, and other computational tools required for technical work?
High-speed internet and suitable computer · required
Are you located in or authorized to work from the United States, Canada, or the United Kingdom?
US, Canada, or UK location · preferred

0 of 6 answered

Included with this listing

Interview prep — 11 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: Can you isolate a concrete flaw from your own or peers' work, describe its nature precisely, and explain why it matters—not just 'the math was wrong' but the specific way dimensional analysis, conservation laws, or methodological rigor failed?
A strong answer: The answer names a specific paper, describes the error in technical terms (e.g., 'they dropped a factor of 2π in the phase space integral' or 'the boundary condition assumption was unstated'), explains the physical consequence, and shows how you communicated the fix—peer review, conversation, or publication erratum.
Where people lose it: Vague answers like 'I found some issues with the derivation' or 'the assumptions weren't clear' don't prove you can isolate and articulate flaws. Answers that blame the author's competence rather than pinpointing the error signal you'll struggle to give constructive feedback.