What the work involves
You are asked to act as a referee, not a solver. A typical task presents two or more competing derivations, interpretations, or solution paths to the same physics problem, and you decide which holds up — under what assumptions, in which regimes, and where each approach breaks. Much of the value is in the meta-level reasoning: naming the approximation that quietly fails, the limit that was taken in the wrong order, the boundary condition that was never justified.
Deliverables are written and self-contained. Expect to produce evaluations that a fellow senior physicist in your subfield could read and either endorse or contest on the record — LaTeX for anything algebraic, and SymPy, Python, or Jupyter when you want to check a claim numerically or symbolically rather than assert it. Calibrated confidence matters as much as correctness: tasks explicitly reward saying "this is genuinely open in the field, and here is why" over manufacturing a verdict.
What the platform screens for
- Verified seniority. micro1 looks for a physics PhD plus independent research leadership — Associate Professor or above, Chair Professor, or PI/group leader — typically evidenced by 3–5 recent representative papers with arXiv or DOI links in your named subfield.
- Subfield specificity. Active research in one of: high energy physics, mathematical physics, biophysics, statistical physics, condensed matter, AMO/quantum optics, gravitation, cosmology, astrophysics, quantum information, or optical properties of materials. Generalist claims tend not to survive follow-up questioning.
- Adjudication instinct. Screens probe whether you can compare two approaches on assumptions and validity regimes rather than restating textbook results.
- Writing under scrutiny. Prose is assessed for whether it would survive peer review, not whether it sounds authoritative.
No prior AI or machine learning experience is required or expected; domain judgment is the deliverable.
Logistics
Fully remote contractor engagement, asynchronous, with no fixed hours. Volume fluctuates with customer demand — most contributors treat this as a supplement to an existing academic post, working in blocks of a few hours across the week. Tooling gaps (e.g., limited SymPy experience) are worth stating plainly during screening rather than overstating; they are usually workable.