Computational Mathematics Researcher (Task Author)

About the role

<p>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.</p>

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

<p>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.</p>

<p>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.</p>

<p><strong>Requirements</strong></p>

<ul>

<li>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.</li>

<li>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.</li>

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

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

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 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