MercorDomain experts
High Energy Physicist (PhD)
up to $110/hr
About this role, in Mercor's words
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.
A closer look
More context, when you need it.
Full job descriptionThe original posting, in Mercor's words
Posted by Mercor, reproduced here so you can judge the role before clicking. Original posting ↗
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.
Research areas in this panel
Seven areas. We match narrowly: you need to have published on one of these specific phenomena, not in high energy theory broadly. Each area lists the methods it requires.
1. AdS/BCFT, end-of-the-world branes, black hole interiors: AdS/BCFT correspondence, Karch-Randall end-of-the-world branes, geodesic approximation for heavy bulk fields, thermal one-point functions, BTZ black hole geometry, black hole interior behind the horizon.
2. LaMET and quasi-PDFs: matching kernels and DGLAP evolution: Large-momentum effective theory, quasi-parton distribution functions, pion parton distribution functions, perturbative matching kernels, modified minimal subtraction renormalization, plus distributions, DGLAP evolution, renormalization-group resummation of logarithms, one-loop running coupling.
3. LaMET and quasi-PDFs: one-loop perturbative QCD and renormalization: Perturbative quantum chromodynamics, large-momentum effective theory, quasi-parton distribution functions, one-loop Feynman diagram computation, dimensional regularization, MS-bar renormalization scheme, superficial degree of divergence analysis, soft and collinear infrared divergences.
4. LaMET and quasi-PDFs: Coulomb gauge matching and lattice QCD parton structure: Large-momentum effective theory, Coulomb gauge fixing, quasi-parton distribution functions, perturbative matching kernels, one-loop QCD corrections, dimensional regularization, MS-bar renormalization scheme, lattice QCD calculations of parton structure.
5. Ultralight vector (dark photon) dark matter in laser interferometers: Ultralight vector dark matter, dark photon coupled to the baryon-minus-lepton current, laser interferometric gravitational-wave detection, differential test-mass forces from composition-dependent charge-to-mass ratios, strain noise spectral density and detector sensitivity curves, coherent signal integration and signal-to-noise scaling, local dark matter density normalization, coherence time of a stochastic ultralight field.
6. Matrix models and invariant theory: Grassmann-valued invariants, Molien-Weyl and Hilbert series: Adjoint matrix models, Grassmann-valued matrix invariants, gauge-invariant operator counting, trace relations, Cayley-Hamilton identities, Molien-Weyl formula, plethystic Hilbert series, primary and secondary invariants.
7. Superconformal and Witten index, finite-N trace relations, plethystic counting: Witten index, superconformal index, adjoint fermion matrix models, trace relations at finite N, Grassmann-valued matrix invariants, Molien-Weyl formula, plethystic counting of gauge invariants, finite-rank corrections to large-N counting.
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:
• Holographic: AdS/CFT and AdS/BCFT correspondence, geodesic approximation, thermal one-point functions
• Perturbative QCD: one-loop Feynman diagram computation, dimensional regularization, MS-bar renormalization, soft and collinear divergences
• Effective field theory: large-momentum effective theory, perturbative matching kernels, renormalization-group resummation of logarithms
• Lattice: lattice QCD calculations of parton structure, gauge fixing
• Group-theoretic: gauge-invariant operator counting, trace relations, Cayley-Hamilton identities, Molien-Weyl formula, plethystic counting
• Astroparticle and detector: interferometric gravitational-wave detection, strain noise spectral density, signal-to-noise scaling
Who we are looking for
A PhD in high energy theory, nuclear theory or a closely related field. 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.
For the quasi-PDF areas specifically, we need loop-calculation experience, not lattice experience alone.
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. Some familiarity with an agentic coding extension in VS Code is useful. Gaps here 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
• 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.
• We verify your papers and authorship against the public record.
• 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.
• 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.
Working with MercorPay, getting started and work, from Mercor's own pages
What the platform publishes in general. These are not extra terms confirmed for this particular role.
- Getting paid
- Hourly work is paid every Wednesday for the previous week, through Stripe Connect or Wise, whichever Mercor assigns to your region. Stripe holds the first payout for 7 days. talent.docs.mercor.com/how-to/payments, talent.docs.mercor.com/policies/contracts
- Before your first paid task
- An AI interview of about 20 minutes, reused for other roles that need it, then any assessments the role asks for. Before logging hours: ID verification through Persona, a tax form, the contract documents, the Insightful time tracker, and a background check the onboarding guide says usually takes one to two weeks. talent.docs.mercor.com/support/ai-interview, talent.docs.mercor.com/how-to/apply, talent.docs.mercor.com/policies/contracts, talent.docs.mercor.com/how-to/id-verification, talent.docs.mercor.com/working/project-onboarding
- How much work
- Hearing back after the AI interview usually takes 2 to 4 weeks. When a project ends you are not moved to a new one automatically. talent.docs.mercor.com/support/ai-interview, talent.docs.mercor.com/support/project
- Contract
- Independent contractor with Mercor.io Corporation of San Francisco, which deducts no taxes. talent.docs.mercor.com/policies/taxes-work-authorization, talent.docs.mercor.com/support/legal
Read on the pages linked above on 23 Sep 2026. Platforms change these terms, so check the linked page before you rely on one.
Alex's experience on MercorA personal account, not a promise about your project
Alexruns this site and has worked on Mercor himself. Written 31 Aug 2026.
- Every interview I took used an AI interviewer. They always checked my microphone and camera and asked me to share my screen, and some included a timed exercise of around 25 minutes.
- Many later applications needed no new interview from me. With the required assessments complete and no other outstanding steps, applying could be close to one click.
- The application I checked did not ask for a rate. My offer matched my minimum in Work Preferences. That does not establish that Mercor always caps higher offers at your preference.
- Onboarding and setup came to about 4 hours, with more security and tool setup. Of the three platforms I worked on, it was the most complicated for me. That is an estimate from my projects, not a platform average.
- Mercor required the Insightful tracker on my project. I observed app and website usage monitoring, and I am unsure which screenshot settings applied, so check the configuration.
- I was paid for hours logged, once every 14 days, and I have not experienced late or incorrect payments. That was my arrangement. Mercor's current documentation describes weekly payout cycles, so check your own offer.
One person's applications, not a promise about yours.
What happens after you apply, first-handHow does the pay compare?Across Domain experts roles, not this role alone
From our own daily reads of every open listing on the platforms we follow, not from Mercor's posting. How we count.
Pay across the field: Domain experts
Across 698 roles in this field with a stated hourly rate in US dollars, on 18 platforms, the middle half pays $65 to $130 an hour at the top of the range, and the median is $100. This role's top rate, $110, is in the middle half. Of the 260 distinct rates we count, 159 are lower and 93 are higher.
| Platform | Roles | Top of range, per hour |
|---|---|---|
| Alignerr | 149 | $24 to $200 · median $80 |
| micro1 | 136 | $28 to $400 · median $110 |
| AfterQuery | 88 | $45 to $175 · median $100 |
| Handshake AI | 79 | $30 to $300 · median $85 |
| Mercor (this platform) | 77 | $55 to $450 · median $120 |
Sources and listing historyWhere this information comes from
This listing's history
- First seen here on 25 Sep 2026, and still on Mercor's list when we last read it on 13 Oct 2026.
- The listed pay has not changed since then.
- Posted by Mercor
- First seen by AIPayList
- Last seen live
- Listing ID
- list_AAABoNelIXEL_UXJCpdK7qyb
Pay as the source states it: “80–110 USD HOUR”.
Platforms sometimes change a rate after posting. Every listing here is re-read at least once a day and corrected when its source moves, so a difference you see on the platform is usually a change made since the last read. How freshness works.
Keep exploring
More like this
Related field, different requirements. Check each role's own page before you apply.