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Mathematics mercor

Mathematical Physicist (PhD)

Mercor • Remote

Education

PhD

Type

Hourly

Pay Rate

$80–$110/hr

Listed

5d ago

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About this role

From the Mercor listing

About the work

CritPt is a public benchmark of research-level physics challenges, built to test whether frontier AI models can carry out genuine physics research reasoning rather than textbook problem solving. The benchmark paper is arXiv:2509.26574 and we recommend reading it before applying. It will tell you quickly whether this work interests you.

We are engaging physicists to work on research-level physics problems in their own subfield. Depending on where your publication record fits, that can mean creating problems, solving them, reviewing completed work, or auditing it. We agree the specific assignment with you once you are matched to an area.

This is research-grade work rather than volume work. Whatever you produce has to be complete enough for another specialist in your subfield to follow and verify independently, so written reasoning is part of every assignment. In this panel the standard of proof sits closer to mathematics than to physics.

Research areas in this panel

Four areas. We match narrowly: you need to have published on one of these specific phenomena, not in mathematical physics broadly. Each area lists the methods it requires.

1. Special functions: hypergeometric identities and analytic continuation: Gaussian hypergeometric functions, parameter differentiation of special functions, quadratic transformation identities for hypergeometric series, analytic continuation in a series index, digamma-function series, asymptotic and series expansions of special functions.

2. Integrable systems: half-wave maps, Lax pairs, Haldane-Shastry and Calogero-Moser: Half-wave maps equation, Lax pair formalism and isospectral flows, Hilbert transform and singular integral operators, classical Haldane-Shastry spin chain, Calogero-Moser systems, hierarchies of conserved charges, solitons of integrable spin-field equations, numerical quadrature of singular integrals.

3. Permutation combinatorics for random tensor network entanglement (Cayley distance, Weingarten): Cayley distance and geodesics in the symmetric group, minimal factorizations of permutations, non-crossing partitions, replica permutation spin models, random tensor network entanglement entropy, Weingarten calculus, multipartite entanglement measures, combinatorial enumeration of configurations.

4. Conformal geometry: Fefferman-Graham ambient metric, obstruction tensors: Fefferman-Graham ambient metric construction, conformal geometry and Weyl covariance, extended obstruction tensors, Schouten and Weyl curvature tensors, order-by-order solution of Ricci-flatness conditions, poles and residues under dimensional continuation, Poincare-Einstein asymptotic expansions.

Methods we expect to find in your own publications

You should be able to point to your own papers demonstrating at least one of the following families:

  • Special function analysis: Gaussian hypergeometric functions, parameter differentiation, quadratic transformation identities, analytic continuation in a series index, asymptotic expansions

  • Integrability: Lax pair formalism, isospectral flows, Hilbert transform and singular integral operators, hierarchies of conserved charges, numerical quadrature of singular integrals

  • Combinatorial: Cayley distance and geodesics in the symmetric group, minimal factorizations of permutations, non-crossing partitions, Weingarten calculus, multipartite entanglement measures

  • Geometric: Fefferman-Graham ambient metric construction, Weyl covariance, Schouten and Weyl curvature tensors, order-by-order solution of Ricci-flatness conditions, Poincare-Einstein asymptotic expansions

Who we are looking for

A PhD in mathematical physics, theoretical physics or mathematics. This is a hard requirement. Postdoctoral researchers, research scientists and junior faculty are the strongest fit. Senior PhD students with a strong first-author record are welcome to apply.

Published work on the specific phenomenon above, not the adjacent one. This is the single most common reason we decline otherwise excellent physicists. Command of the methods is not enough if you have not published on the phenomenon itself.

A verifiable publication record. Three to five representative papers with arXiv IDs or DOIs, ideally from the last five years. First author strongly preferred. Every paper you list will be checked against the public record.

Working proficiency with LaTeX, Python, SymPy and Jupyter. Symbolic computation matters more in this panel than in most. Some familiarity with an agentic coding extension in VS Code is useful. Gaps there are acceptable if you declare them honestly.

English at B2 or above, including written reasoning. A large part of the value you add is how clearly you set out your argument.

Application steps

  1. Apply and complete the attached form. Basic information, education, research experience, your method self-attestation, and up to five of the areas above that you are the best fit for. For each area you select, give an arXiv ID or DOI of your own paper as proof, with your author position and the methods it demonstrates. A selection without proof is not scored.

  2. We verify your papers and authorship against the public record.

  3. Then one of two things happens. Either we onboard you directly, or we invite you to a short live alignment call to agree the area and the assignment with you.

  4. A brief 30 to 45 minute assessment may be added, but only where we need it. Most applicants will not see one.

Commitment and rate

10 hours per week, sustained across an 8 to 10 week window, starting immediately. Remote and asynchronous with no fixed hours.

$80 to $110 per hour, set by depth of subdomain match.

Requirements

  • Must be eligible to work in Remote
  • Fluent proficiency in English (Written & Verbal)
  • Reliable high-speed internet connection
  • PhD's degree or equivalent professional experience
  • Demonstrated expertise in Mathematics

How long hiring takes

Across the AI training platforms we refer candidates to, the median gap between referral and hire is about 30 days. It varies by platform and role, so treat it as a rough guide for this one.

Within 2 weeks
~25%
Within 6 weeks
~60%
Within 3 months
~80%

Talent Pool members

Apply through this link and we can put you forward to Mercor when your profile is a strong match. Not every applicant is submitted. If you're not in the pool yet, set up your profile first.

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Interview Prep

This listing calls for this tool directly. Prep for the technical screen:

Why this role

This Mathematical Physicist (PhD) role pays $80–$110/hr for your Mathematics judgment directly, without requiring case files, client meetings, or firm overhead to get there.

Talent pool

We're light on Mathematics candidates

We've matched 65 people with a Mathematics background against 726 Mathematics listings we've tracked, so most go out without one. Set up a profile and we'll consider you for a role like this one.

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Skills and categories

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Common questions

Is Mercor for freelancers or full-time contractors?

Mercor places you with one client for a defined engagement, like 'Python Tutor for 3 months', rather than having you grab small tasks from a shared queue. Most roles function as steady contract work, not one-off gigs.

Does Mercor's application require an on-camera interview?

Yes, every applicant records a video interview with an AI interviewer that asks questions about your resume. Clients review that recording to judge communication skills before matching, so there's no way to apply without going on camera.

Why do these AI training roles pay so much?

Because general knowledge isn't what's being tested. The model already knows the basics; what it needs is expertise on edge cases, the rare, difficult, highly technical judgment calls only a senior professional in the field would make correctly.

What does the day-to-day workload look like for elite-expert AI training roles?

Slow and deep, not fast and repetitive. A single task can take 45-60 minutes of researching citations or verifying complex calculations. Quality is what's being measured here, not throughput.

What does Mathematics work look like for a Mathematical Physicist (PhD)?

Tasks here are scoped to Mathematics, not generic labeling. As a Mathematical Physicist (PhD), expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Mathematics) rather than following a one-size-fits-all rubric. If you don't have hands-on Mathematics background, this is likely not the right listing to start with.

What specific skills does this listing call for?

Coding, Python, English, and PhD are named directly in the listing. If you don't have hands-on experience with these, expect the screening process to test for them directly rather than accepting adjacent experience as a substitute.

How much does this specific role pay?

This listing is posted at $80–$110/hr, an hourly rate. The range reflects experience level and negotiated terms, not a placeholder, so where you land in it depends on your background and the assessment. Pay can change between when we last checked the listing and when you apply, so confirm the current number on the platform's own application page before committing time.

What happens when I click Apply on this listing?

You'll be taken to Mercor's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.

Is a PhD required?

For this specific role, yes, or near-equivalent professional depth. The credential gate is enforced at the assessment stage, not just on paper. That said, active PhD candidates and people with equivalent published research have qualified without a formal degree. The assessment is the real filter.

How soon will I start working after applying to Mercor?

Not immediately. Mercor is a talent marketplace, not a task queue, so applying puts you in a pool of candidates. You start working only once a specific client, like a major AI lab, selects your profile, and that matching process can take weeks.