Computational Materials Science Researcher (Task Author)

Turn computational work from your own materials science 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 phase-field or CALPHAD model, an atomistic simulation, a microstructure or diffraction analysis, or a transport calculation 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 materials science itself, not from withheld information. We're looking for researchers in: electronic and quantum materials; semiconductors and optoelectronics; metals, alloys, and computational metallurgy; polymers and soft materials; ceramics and glasses; mechanical behavior and structural materials; thermal transport and lattice dynamics; battery and energy materials; surfaces, interfaces, and nanomaterials; and materials informatics. 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 materials science, physics, chemistry, mechanical engineering, or a closely related field. Technical: Hands-on experience writing your own code, preferably Python, to model materials or analyze materials data. Running standard packages without your own scripting 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.