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Earth, Ocean & Climate Science Researcher (Task Author)

Turn your earth, ocean, or climate research into Python tasks that test AI models. This flexible contractor role pays $200 per approved task, with each task taking about two hours.

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OpenTrain AI

Coding & Software

Remote

Contract

Engagement

Remote

Location

Nov 8, 2026

Posted

Open in 95 countries

United States
+ more
  • Albania
  • Algeria
  • Antigua and Barbuda
  • Armenia
  • Australia
  • Austria
  • Bahamas
  • Bahrain
  • Belgium
  • Benin
  • Bhutan
  • Bosnia and Herzegovina
  • Botswana
  • Brunei
  • Bulgaria
  • Canada
  • Costa Rica
  • Côte d’Ivoire
  • Croatia
  • Cyprus
  • Czechia
  • Denmark
  • Ecuador
  • El Salvador
  • Estonia
  • Ethiopia
  • Finland
  • France
  • Gambia
  • Germany
  • Greece
  • Guatemala
  • Guyana
  • Hong Kong
  • Hungary
  • Iceland
  • India
  • Indonesia
  • Ireland
  • Israel
  • Italy
  • Jamaica
  • Jordan
  • Kenya
  • Kuwait
  • Latvia
  • Liechtenstein
  • Lithuania
  • Luxembourg
  • Madagascar
  • Malaysia
  • Malta
  • Mauritius
  • Mexico
  • Moldova
  • Mongolia
  • Morocco
  • Mozambique
  • Namibia
  • Netherlands
  • New Zealand
  • North Macedonia
  • Norway
  • Oman
  • Pakistan
  • Panama
  • Peru
  • Philippines
  • Poland
  • Portugal
  • Qatar
  • Romania
  • Rwanda
  • Saint Lucia
  • Senegal
  • Serbia
  • Singapore
  • Slovakia
  • Slovenia
  • South Africa
  • Spain
  • Sri Lanka
  • Sweden
  • Switzerland
  • Taiwan
  • Tanzania
  • Thailand
  • Trinidad and Tobago
  • Tunisia
  • Türkiye
  • United Arab Emirates
  • United Kingdom
  • United States
  • Uzbekistan
  • Vietnam

The work

Create and validate research-grade scientific-computing tasks based on computational work you have personally run and debugged. Your tasks will help evaluate whether AI models can reason about real scientific problems and produce working solutions.

You may work on geophysical inversion, ocean or atmosphere modeling, data assimilation, remote sensing, hydrology, geodynamics, or climate science. Each task includes a main problem, connected subproblems, a Python reference solution, and tests that check the results.

You will also define useful quality metrics, revise tasks based on structured review feedback, and may review and calibrate tasks submitted by other experts in your field.

  • Create original tasks from your own computational research.
  • Write Python reference solutions and tests.
  • Define metrics for judging solution quality.
  • Revise tasks after structured review feedback.
  • Optionally review and calibrate tasks from other experts.

What it pays and takes

This is flexible, task-based independent-contractor work with no fixed weekly schedule. Each task takes about two hours, and there is no stated limit on the number of tasks you can complete.

  • Pay: $200 per approved task.
  • Schedule: Flexible and task-based, with no fixed weekly schedule.
  • Location: Open to candidates in the countries listed for this role.
  • Language: Fluent English.
  • Experience: Research-track Bachelor's students with research experience, current Master's or PhD students, postdoctoral researchers, and related researchers may apply.
  • Education and fields: Geophysics, oceanography, atmospheric science, geology, hydrology, climate science, or a closely related field.
  • Skills: Hands-on experience writing your own code, preferably Python, to model or analyze earth, ocean, or atmospheric systems.
  • Requirements: Ability to turn computational research into a clear task with a reference solution and tests, work independently, and manage your own time.
  • Work authorization: Independent-contractor work authorization without visa sponsorship is required.
  • Helpful background: Data assimilation, ocean or atmosphere modeling, seismic inversion, public research code, a thesis, scientific papers, data annotation, data labeling, or AI and machine-learning evaluation.

How it works

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

About AI training work

AI training is the human work behind better artificial intelligence. Researchers and other specialists create examples, tests, and reviews that show AI systems how to solve problems, and experienced contributors are paid for the subject knowledge and careful validation this work requires.

Requirements

  • Languages: English

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