$84/hrAs published by the platform.
This role involves evaluating demanding atomistic simulation and materials science problems, and checking AI-generated answers on topics such as DFT and molecular dynamics. It is aimed at PhD-level specialists in computational materials science, quantum simulation, or molecular modelling who want to improve how AI reasons about materials.
$84/hr
Pay as published by the platform. It is not a guarantee of income or hours.
Open to residents of: United States.
You apply on work.mercor.com: create a profile, complete a skills assessment, then get matched to projects that fit your background.
Official posting: https://work.mercor.com/jobs/list_AAABoSrPUxxXD7fJaeFCSrmf/atomistic-materials-modeling-expert
Last checked on October 12, 2026.
Mercor is recruiting scientists and engineers specialized in inorganic synthesis, materials characterization, superconductors and semiconductors to support a cutting-edge AI research laboratory. You will contribute to generating, structuring and evaluating high-quality scientific data intended for model training, by applying your deep expertise to complex problems in materials physics.
Posted August 1, 2026
This remote contract role asks materials science specialists to write and check demanding problems that test how AI models reason about semiconductor materials and molecular modeling. It is aimed at Master's and PhD holders, including working researchers, academics and industry experts. Candidates review AI-generated scientific answers and help close their gaps, and no prior AI experience is required.
This remote contract role asks materials science experts to help train and evaluate AI models on semiconductor materials, molecular modeling, and other advanced materials problems. It is aimed at researchers with a master's or doctoral background who can write and review scientifically rigorous problems. No prior AI experience is needed because training is provided.
This role asks inorganic chemistry and materials synthesis experts to assess complex scientific problems, check AI-generated chemistry reasoning, synthesis routes and experimental methods, and help make AI models more reliable on scientific reasoning. It suits PhD-level researchers and materials scientists with hands-on experience designing, synthesising and characterising inorganic materials.
Posted October 11, 2026
This ongoing project hires advanced STEM experts to write graduate-level and PhD-level problems with exact, verifiable answers, helping AI systems improve at rigorous scientific reasoning. Participants create original problems in their own specialty, write detailed step-by-step solutions, and sometimes review AI-generated answers to find reasoning errors. It is aimed at PhD candidates and holders, postdoctoral researchers, and faculty in biology, chemistry, physics, mathematics, and selected engineering fields.
Posted August 6, 2026
This role involves evaluating AI-generated chemical reasoning and responses to identify flawed mechanisms, unsafe procedures, and analytical errors. You will write prompts to test chemical knowledge, review AI outputs for errors, and provide correct expert-level answers with proper attention to safety and experimental conditions.
