Materials Research Coding Benchmark Author
IXO is engaging specialists to evaluate materials-science coding tasks with research-level scientific checks. Your contribution is technical work: make the reasoning inspectable, identify substantive errors and provide evidence that supports a reliable assessment.
Work you will do
- Turn a substantive materials problem into a runnable computational task with explicit inputs, outputs and scientific assumptions.
- Develop or verify a reference implementation, reproduce the environment and test that the scientific result is correct.
- Explain the physics or chemistry behind the computation and review alternative solutions against objective evaluation criteria.
Required background and routes
- A completed PhD in materials science/engineering, applied physics, chemistry, chemical engineering or a closely related discipline, with demonstrated depth in both semiconductor materials and molecular modelling.
- Scientific programming in Python or R (another suitable scientific language is acceptable for the science tracks); use Git/GitHub and Docker to submit reproducible work through pull requests and automated checks.
Preferred background
- Peer-reviewed publications, research software development or research-engineering experience.
Deliverables
Submit the completed technical artifact or assessment with its supporting evidence, explicit assumptions, reproducible checks where applicable, and concise reasons for each material judgment. Address review findings within the agreed scope.
Location and schedule
Remote assignments are scheduled by agreement, with no guaranteed weekly volume. Availability planning can include 40, 20 hours per week depending on the track. Indicative assignment lengths include 6 weeks. IXO confirms the applicable timing before work.
Pay and working terms
$75/hr USD. The agreed hourly rate, scope, schedule and acceptance criteria are confirmed before work starts. Applying does not guarantee an assignment. Use public, licensed or otherwise authorized material only; do not submit confidential employer information, personal data or restricted research.
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