Environmental Research - Graduates - AI Training - UK in Edinburgh

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.

What you’ll bring:

• 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.
• PayPal account to receive payment from our clients.

What you’ll be doing in the role:

• 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).