Computational Mathematics Researcher (Task Author)

About this role

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.

Skills & domains

• ai-training
• expert