Computational Materials Science Researcher (Task Author)

$100/hr

rate as listed

Workload: ~15h/week
Engagement: Project-based
Location: Worldwide
Field: Sciences

Turn computational materials research you have personally implemented and debugged into evaluation tasks for AI models. Each task requires a well-specified problem, connected subproblems, a reference solution, and tests grounded in genuine materials science.

The work

Authors adapt computational work from their own research into self-contained scientific evaluation tasks. Suitable source material includes phase-field or CALPHAD models, atomistic simulations, microstructure or diffraction analysis, transport calculations, and related work across electronic materials, semiconductors, metallurgy, polymers, ceramics, structural materials, batteries, interfaces, nanomaterials, and materials informatics. Each task includes a main problem, connected subproblems, a reference solution, and tests; Python is preferred.

What the platform screens for

The screen focuses on whether you personally wrote and debugged code for materials modeling or data analysis, rather than only running standard packages. Expect follow-up questions about model assumptions, implementation choices, validation, failure modes, and how you would make a research problem complete without withholding information. Public code, a thesis, or papers can help verify this experience but are preferred rather than required.

Practical details

This is flexible, independent-contractor work with no fixed weekly schedule. A task is expected to take about two hours, then may require revisions following structured review; reviewing other experts' submissions is optional. The listing does not explicitly identify the role as remote, though the authoring and review workflow is task-based and appears asynchronous. Candidates must be able to contract without visa sponsorship, and accepted experts undergo background and identity verification.

Pay band: $100/hr

What they look for

Hands-on experience writing original code to model materials or analyze materials data
Computational research experience in materials science, physics, chemistry, mechanical engineering, or a closely related field
Ability to convert completed research work into a self-contained problem with subproblems
Reference-solution development and scientific test design
Validation, debugging, and evaluation of numerical or data-analysis workflows
Python, preferred for reference solutions and task implementation

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: This establishes whether your education or research status matches the listed pathways and whether the proposed task source is genuinely your own computational work.
A strong answer: Name the program or role, field, research setting, and one concrete project, then separate your own implementation responsibilities from those of an adviser or collaborator. Include an artifact such as a thesis, repository, paper, poster, or reproducible result when available.
Where people lose it: Candidates lose points by describing a lab's broad research program without identifying the code, model, or analysis they personally built.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

What you'll need

Hands-on experience writing original code to model materials or analyze materials data

Computational research experience in materials science, physics, chemistry, mechanical engineering, or a closely related field

Ability to convert completed research work into a self-contained problem with subproblems