Expert Work

Computational Mathematics Researcher (Task Author)

Status: Open

AfterQuery

Pay
$100/hr
Location
Remote
Employment type
Contract
Posted
2026-10-16

About this opportunity

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.

What you'll do

  • 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
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