Computational Mathematics Researcher (Task Author)

Turn computational work from your own math research into paid evaluation tasks for AI models. Open to research-track Bachelor's students, Master's and PhD students, postdocs, and recent graduates.

AfterQuery is building a network of researchers to author and validate research-grade scientific-computing tasks for AI models.

A strong task is a real piece of computational work from your own research, something you've actually run and debugged: a numerical solver, an optimization routine, a simulation, a statistical model, or an algorithm you implemented and validated. Each task has a main problem, a few connected subproblems, a Python reference solution, and tests that check the result. The difficulty should come from the mathematics itself, not from withheld information.

We're looking for researchers in: numerical analysis and scientific computing; numerical linear algebra; differential equations and dynamical systems; optimization and operations research; probability, stochastic processes, and uncertainty quantification; computational statistics; discrete mathematics and algorithms; computational geometry, topology, and number theory; and inverse problems.

Requirements

• Education: A Bachelor's student on a research track or with research experience (such as an REU, a thesis, or an RA or lab role), a Master's or PhD student, a postdoc, or a recent graduate in mathematics, applied mathematics, statistics, or a closely related field.
• Technical: Hands-on experience writing your own code, preferably Python, to implement or validate mathematical methods. Familiarity with Python or machine learning alone isn't enough.
• Work authorization: Must be able to work as an independent contractor without visa sponsorship. Students on F-1 visas (including OPT/CPT) are not eligible.

Contract and pay

Flexible, independent-contractor work: $200 per approved task, about 2 hours each, with no cap on how many tasks you take on. Tasks go through review, and you may also review other experts' tasks against a short rubric.

All accepted experts undergo standard background and identity verification.

Responsibilities

• Design and author original research-grade evaluation tasks based on your own computational work
• Specify the metrics a strong solution should be judged by, without publishing the exact passing thresholds
• Revise tasks based on structured review feedback until they're approved
• Optionally review and calibrate tasks submitted by other experts in your domain

Requirements

• Bachelor's student on a research track or with research experience, Master's or PhD student, postdoc, or recent graduate in mathematics, applied mathematics, statistics, or a closely related field
• Has written their own code, preferably in Python, to implement or validate mathematical methods
• Able to turn your own computational research into a well-specified task with a reference solution and tests
• Able to work independently and manage your own time. This is flexible, task-based work with no fixed weekly schedule

Preferred Qualifications

• Research experience in numerical methods, optimization, stochastic processes, or computational topology or number theory
• Public code, a thesis, or papers that show your computational work
• Prior experience in data annotation, data labeling, or AI/ML evaluation work

Why Apply

• Work on your own schedule: task-based, not a fixed hourly commitment
• Contribute directly to how AI models are evaluated on real, expert-level scientific work
• Paid, flexible work: $200 per approved task (about 2 hours each), no cap on how many you take on