Scientific Researcher

Author research-grade AI evaluation tasks from your own computational work. Open to PhD students, postdocs, research scientists, and research-active Master's students. 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, debugged, or been paid to do: simulation setup, numerical solvers, model fitting, data reduction, analysis pipelines, or inverse problems. Each task has a main problem, a few connected subproblems, a reference solution, and tests that check the scientific result. The difficulty should come from the science itself, not from withheld information. We're especially looking for researchers in: bioinformatics and computational biology; quantum physics and computational astrophysics; materials science and molecular/quantum chemistry (including electronic structure, polymers and soft matter, chemical kinetics and spectroscopy); condensed-matter and statistical physics; particle and plasma physics; and geochemistry, remote sensing, oceanography, and coastal modeling. Requirements

Education:
Currently pursuing or holding a PhD with active hands-on research, or a Master's (current or completed) with a research-active record: thesis research, an RA or lab role, a publication, or a clear PhD trajectory. Technical: Working proficiency in Python, enough to run and debug your own computational work. 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 Required Qualifications
• Currently pursuing or holding a PhD with active hands-on research, or a Master's with a research-active record: thesis-based enrollment, an RA or lab role, a real publication, or a clear PhD trajectory
• Working proficiency in Python, enough to run and debug your own computational work
• Able to turn your own computational research work into a well-specified evaluation task
• Able to work independently and manage your own time. This is flexible, task-based work with no fixed weekly schedule Preferred Qualifications
• Current PhD student, postdoc, or faculty actively publishing in your field
• Demonstrated experience in scientific computing, data analysis, simulation, or numerical methods
• 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