Environmental Research - Graduates - AI Training

Remote

We're looking for Environmental Researchers and Sustainability Experts to join our Expert Network to help train and evaluate cutting‑edge AI models using real‑world ecological and climate expertise. If you have the necessary experience, we’ll send you a quick 10‑ to 15‑minute test to assess your skills and suitability for AI tasks. If successful, you’ll be invited to join Prolific as a participant, where you’ll get paid to train and evaluate powerful AI models.

Researchers looking for your skills typically pay up to $45–$90 per hour
. You must be prepared to complete paid tasks that require one hour of uninterrupted work
, though many are shorter.

• Education: a BS, MS, or PhD in Environmental Science, Ecology, Climate Science, Environmental Engineering, or a related field.
• Professional
  
  Experience:
  
  experience in environmental impact assessment (EIA), climate modeling, conservation research, or corporate sustainability reporting (ESG).
• Domain Knowledge: deep understanding of carbon accounting, biodiversity metrics, renewable energy systems, or environmental policy.
• Analytical Precision: the ability to identify errors in climate data interpretations, carbon footprint calculations, or ecological taxonomies.
• Geospatial & Statistical Literacy: proficiency in interpreting GIS data, satellite imagery, and longitudinal environmental datasets.
• Communication: ability to synthesize complex environmental regulations or scientific findings into clear, actionable, and technically accurate summaries.
• A Pay Pal account to receive payment from our clients.

• Evaluate AI‑Generated Research: review model responses to queries about climate change, ecosystem services, and resource management for scientific accuracy and nuance.
• Fact‑Check Environmental Claims: validate AI‑generated data regarding emissions factors, legislative requirements, and environmental protection standards.
• Assess Sustainability Logic: critique AI‑proposed solutions for waste reduction, supply chain sustainability, and habitat restoration for practical and scientific feasibility.
• Annotate Geospatial & Technical Data: identify and correct errors in model‑generated maps, environmental risk assessments, and species distribution models.
• Ensure Policy Alignment: verify that AI responses align with the latest international environmental standards and scientific consensus (e.g., IPCC reports).