Scientific Computing Evaluation Task Author

Work you will do

• Turn a genuine data-reduction, model-fitting, simulation, instrument-processing, numerical-solver or inverse-problem workflow into a well-specified task.
• Run and debug the Python-based work, ensuring that the challenge comes from the science rather than missing information.
• Describe the evaluation metrics without exposing exact passing thresholds, and revise the task in response to specific review findings.
• Where assigned, review or calibrate other scientific tasks within your own domain.

Required background and routes

• A current or completed PhD with active practical research, or a research-active master's profile supported by a thesis, laboratory/RA role, publication or clear doctoral trajectory.
• Use Python well enough to execute/debug your research and turn authentic computational work into a clearly specified assessment. An industry-only master's background without research does not meet this route.

Preferred background

• Current publication activity as a doctoral student, postdoc or faculty member; simulation, numerical methods or data-analysis experience; previous annotation or AI-evaluation work.

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

Tasks have no fixed weekly schedule. A reference task is estimated at around four hours, but the payment is for the accepted task rather than time spent.

Pay and working terms

$310/task USD. Payment is for a completed task that meets the agreed acceptance criteria. The fee, task specification and revision requirements are agreed before work; an advertised time estimate does not determine payment. 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.