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 workSpecify the metrics a strong solution should be judged by, without publishing the exact passing thresholdsRevise tasks based on structured review feedback until they're approvedOptionally review and calibrate tasks submitted by other experts in your domain Required Qualifications 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 fieldHas written their own code, preferably in Python, to implement or validate mathematical methodsAble to turn your own computational research into a well-specified task with a reference solution and testsAble 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 theoryPublic code, a thesis, or papers that show your computational workPrior experience in data annotation, data labeling, or AI/ML evaluation work Why apply Work on your own schedule: task-based, not a fixed hourly commitmentContribute directly to how AI models are evaluated on real, expert-level scientific workPaid, flexible work: $200 per approved task (about 2 hours each), no cap on how many you take on