The work

You would design challenging scientific problems with verifiable solutions, then review AI-generated answers for factual accuracy, methodological rigor, and depth of reasoning. Day-to-day tasks may include writing reference answers, building scoring rubrics, checking claims against primary literature, documenting subtle scientific errors, and revising work through feedback and peer review.

Scientific scope and screening

The platform is likely to verify your PhD research, individual contributions, publications or other research outputs, and command of relevant methods under detailed follow-up. Relevant areas include molecular simulation, free energy methods, protein structure prediction and design, docking and virtual screening, QSAR/QSPR and ADMET modeling, cheminformatics, proteomics, metabolomics, and molecular machine learning. Preferred tool experience includes GROMACS, AMBER, NAMD, OpenMM, AlphaFold, Rosetta, AutoDock, Glide, Schrödinger Suite, MOE, RDKit, MaxQuant, and LC-MS/MS workflows.

Communication and programming

Professional written and spoken English at C1 or higher is required. Python is required in practice, while R and Bash are additional listed programming languages. Strong performance depends on explaining assumptions, validation choices, uncertainty, and failure modes clearly enough for another expert to reproduce or audit the reasoning.

Logistics

This is a contractor role open remotely worldwide. The listing does not specify whether work is fully async or state typical weekly hours, so candidates should confirm scheduling, workload, and turnaround expectations during screening. Pay band: $45–90/hr