$20-$50 per hour
Hourly contract
Remote
Mercor is seeking PhDs and PhD candidates in Chemical Engineering and related disciplines to join a high-impact AI research initiative with a leading AI lab. This role involves evaluating and improving cutting-edge large language models (LLMs) by contributing deep domain expertise and academic research insight to benchmark model performance in chemical engineering and technical disciplines.
Evaluate the accuracy, depth, and relevance of LLM-generated responses in your domain of expertise: Fluid Flow and Heat Transfer in Chemical Engineering, Mass Transport and Separation Processes, Chemical Reaction Engineering.
Design and review complex domain-specific tasks to rigorously test model capabilities.
Provide structured, high-quality feedback on model strengths and weaknesses.
Collaborate with AI researchers to identify model limitations and suggest improvements.
Contribute to the development of benchmark datasets and evaluation protocols.
A PhD (or are currently a PhD candidate) in Chemical Engineering, Process Engineering, or a related STEM field.
Deep familiarity with current research, industrial applications, and open questions in:
Transport phenomena (momentum, heat, and mass transfer)
Reactor engineering and chemical kinetics
Separation technologies (distillation, extraction, adsorption, etc.)
The ability to critically evaluate scientific reasoning, technical writing, and data-driven insights.
Strong analytical thinking and attention to detail.
Excellent written communication skills.
Comfort working independently and asynchronously in remote teams.
Part-time (10–20 hours/week), fully flexible hours.
100% remote and asynchronous—work on your own schedule from anywhere.
Hourly contractor role via Mercor.
Competitive pay based on expertise and domain, ranging from $20 to $50 per hour.
Payments processed weekly through Stripe Connect.
We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.
Tagged as: Chemistry, Computer Science, Data Science, Earth Science, Engineering, Environmental Science, Life Sciences, Mathematics, Physics
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