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STEM mercor

Quantum Information Science 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.

Research areas in this panel

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

1. Distributed quantum sensing and metrology with GHZ probes under noise: Distributed quantum sensing, quantum Fisher information, Greenberger-Horne-Zeilinger entangled probe states, GHZ-diagonal noisy states, Lindblad master equations, multiparameter phase estimation, entanglement distribution in quantum networks.

2. Quantum optics: two-mode squeezing, SU(1,1) interferometry, homodyne detection with loss: Optical parametric amplification, two-mode squeezed vacuum, two-photon formalism for sideband modes, Bogoliubov transformation of field operators, SU(1,1) nonlinear interferometry, cascaded phase-sensitive amplification with intermediate loss, balanced homodyne detection of quadrature sidebands, beam-splitter model of optical loss and detection inefficiency.

3. Quantum Shannon theory: Holevo and accessible information, classical capacity: Holevo information, accessible information of quantum ensembles, classical capacity of quantum channels, classical-quantum states, von Neumann entropy, optimality conditions for information-maximizing ensembles, convex optimization over probability distributions.

4. Holographic codes and random tensor networks, Haar averaging over O(N): Non-isometric holographic codes, Haar averaging over the orthogonal group, Weingarten calculus, random tensor network models of holography, moments of random linear maps, post-selection onto fiducial states, black hole interior reconstruction.

5. Matrix product states, sequential generation, holographic quantum simulation: Matrix product states, finitely correlated states, sequential generation of matrix product states, isometric tensor network circuits, transfer-matrix formalism for correlation functions, exponential decay of correlations, holographic quantum simulation, bond dimension and entanglement structure.

6. Eigenstate-to-Hamiltonian construction, commutant algebras, integrals of motion: Eigenstate-to-Hamiltonian construction, symmetric Hamiltonian construction from integrals of motion, quantum covariance matrix method, commutant algebras of local Hamiltonian families, Pauli string operator bases, Jordan-Wigner transformation, exact diagonalization of spin chains.

7. Quantum-limited imaging and superresolution: QFI, spatial-mode demultiplexing: Quantum Fisher information, quantum Cramer-Rao bound, Sudarshan-Glauber P representation, mutual coherence matrix of thermal sources, point spread function and diffraction-limited imaging, weak-source single-photon regime, spatial-mode demultiplexing, direct imaging and the Rayleigh resolution limit.

8. Quantum walks and spatial search on graphs, degenerate perturbation theory: Continuous-time quantum walk, spatial search on graphs, graph adjacency matrix spectra, simplex of complete graphs and truncated simplex lattices, degenerate perturbation theory, symmetry-reduced invariant subspaces, critical jumping rate and avoided level crossing.

9. Quantum foundations: higher-order interference, Sorkin parameter, GPTs as information resource: Higher-order interference, Sorkin parameter, multipath single-particle interferometry, spatial superposition as an information resource, generalized probabilistic theories, classical correlation polytopes, fingerprinting inequality, single-particle multiple access channels.

10. Quantum foundations: generalized noncontextuality, KCBS, ontological models: Generalized noncontextuality, Kochen-Specker contextuality, KCBS inequality, noncontextual ontological models, generalized probabilistic theories, simplex embedding, linear programming for nonclassicality, unsharp measurements and POVMs, white-noise robustness.

11. Quantum Shannon theory: private states, quantum and private capacity, superactivation: Private states and private bits, Choi-Jamiolkowski channel-state duality, quantum capacity and coherent information, private capacity of quantum channels, Werner states and symmetric subspace projections, degradable and antidegradable channels, superadditivity and superactivation of quantum capacity, spin alignment conjecture.

12. Quantum relative entropy, strong data processing, contraction coefficients of qubit channels: Quantum relative entropy, data processing inequality for relative entropy, contraction coefficients of quantum channels, strong data processing inequalities, qubit amplitude damping channel, monotone Riemannian metrics and the Bogoliubov-Kubo-Mori metric, Bloch-sphere representation of qubit channels, trace-distance contraction bounds.

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:

  • Entropic and information-theoretic: von Neumann entropy, Holevo bound, coherent information, contraction coefficients, Choi-Jamiolkowski duality
  • Open quantum systems: Lindblad master equations, quantum channels, degradable and antidegradable channels, amplitude damping and dephasing models
  • Random matrix and Haar integration: Weingarten calculus, moments of random linear maps, Haar averaging over the orthogonal group
  • Tensor network: matrix product states, transfer-matrix formalism, isometric tensor network circuits, exact diagonalization of spin chains
  • Convex and geometric: convex optimization over probability distributions, simplex embedding, correlation polytopes, linear programming for nonclassicality
  • Estimation theory: quantum Fisher information, quantum Cramer-Rao bounds, multiparameter phase estimation

Who we are looking for

A PhD in quantum information, quantum optics 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. Having applied the information-theoretic toolkit elsewhere is not enough if your papers are not on the phenomenon in question.

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

  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 STEM

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

$80–$110/hr for Quantum Information Science Physicist (PhD) work puts your STEM expertise on the same footing as an AI lab's own research staff, without the overhead of running a consulting practice around it.

Talent pool

We're light on STEM candidates

We've matched 65 people with a STEM background against 726 STEM 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

Does it cost money to apply to Mercor?

No, applying and joining Mercor is free. Mercor's revenue comes from a fee it charges the client on top of your hourly rate, not from applicants. Treat any request for payment to join as a red flag.

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.

Is AI training work the same as traditional consulting?

No. Instead of client deliverables, you're given complex scenarios to evaluate: grading the AI's logic, correcting its hallucinations, and supplying expert-level reasoning it doesn't have on its own. The job is closer to teaching than consulting.

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 STEM work look like for a Quantum Information Science Physicist (PhD)?

Tasks here are scoped to STEM, not generic labeling. As a Quantum Information Science Physicist (PhD), expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to STEM) rather than following a one-size-fits-all rubric. If you don't have hands-on STEM 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.