Computational Materials Science Researcher Task Author

You will turn computational materials research you have personally completed into clear tasks for evaluating AI models. Each task should include connected subproblems, a Python reference solution, tests, and clear standards for judging the results.

You will revise your work after structured feedback and may review tasks submitted by other experts in your area.

• Design original evaluation tasks based on materials research you have implemented, run, debugged, and validated.
• Create meaningful metrics and review criteria that do not depend on hidden information.
• Write Python reference solutions and tests that check computational results.
• Work may involve phase-field or CALPHAD modeling, atomistic simulation, microstructure or diffraction analysis, transport calculations, electronic and quantum materials, semiconductors, metals and alloys, polymers, ceramics, energy materials, or materials informatics.

This is flexible independent-contractor work with no fixed weekly schedule. You should be able to work independently and manage your own time.

• $100 per hour.
• Approved tasks are described as $200 each and take about two hours per task.
• Open to candidates in the countries listed for this role, including the United States, Canada, Australia, India, and Vietnam.
• Professional fluency in English is required.
• Independent-contractor work authorization without visa sponsorship is required. F-1 students, including OPT and CPT participants, are not eligible.
• Eligible backgrounds include research-track bachelor's study with research experience, current master's or PhD study, postdoctoral experience, or recent graduation in materials science, physics, chemistry, mechanical engineering, or a closely related field.
• Hands-on experience writing your own code, preferably in Python, for materials modeling or materials-data analysis is required.
• You must be able to turn your own computational research into a clear task, reference solution, and test suite.
• Public code, a thesis, or papers showing work you completed yourself are helpful.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training is the human work behind systems that learn from examples, including writing, testing, and reviewing code. OpenTrain helps people find these projects, build a profile, and apply for work that matches their skills.