AI training contract
Computational Chemistry, Structural Biology & Drug Discovery Scientist (PhD)
Engineering · USD 45-90 an hour. · 50 openings
Computational Chemistry, Structural Biology & Drug Discovery Scientist (PhD) is contract work for micro1, reviewing and correcting what AI models produce in engineering. The output of the job is expert judgement written down: a model gives an answer, someone who knows the subject decides whether it is right and explains why.
What it requires. This role is gated on phd or academic credential. Applications without it are not considered, and the requirement is stated here because the original advert usually carries it well below the rate.
What it pays. USD 45 to USD 90 an hour, as published by micro1. Rates in this category track how rare the credential is rather than how hard the work is.
Where. The listing says this role is global and fully remote. micro1 says it hires talent from around the world, except people who reside in Afghanistan, Belarus, China, Cuba, Democratic Republic of the Congo, Hong Kong, Iran, Iraq, Libya, Macao, Myanmar, North Korea, Russian Federation, Somalia, South Sudan, Sudan, Syria, Venezuela, Ukraine, Yemen, and Ethiopia. That rule comes from micro1's own FAQ at www.micro1.ai/experts, read on 2026-10-05. Requirements can still differ by role, so check the application page on micro1 before you apply.
micro1 lists 50 openings on this role.
Skills named: Computational Chemistry, Structural Bioinformatics, Cheminformatics, Proteomics & Metabolomics, Documentation, Verbal communication, Drug Discovery, Biology, Metagenomics.
Applications are made on micro1, not here. WFA Digital is independent of micro1 and may receive a referral fee if you are hired, at no cost to you.
Full listing, as published by micro1
Role Title: Computational Chemistry, Structural Biology & Drug Discovery Scientist (PhD) Role Type: Contractor Location: Remote (Worldwide) Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. Key Responsibilities Design and write challenging, expert-level scientific problems in computational chemistry, structural biology, and drug discovery, with clear, verifiable solutions. Review and evaluate AI model outputs for scientific accuracy, rigor, and depth of reasoning, identifying subtle errors that non-specialists would miss. Develop detailed rubrics and reference answers grounded in the primary literature and established methodology. Apply domain expertise across areas such as molecular modeling and simulation, protein structure prediction and design, virtual screening and docking, QSAR/ADMET modeling, and proteomics/metabolomics data analysis. Provide clear written explanations of your reasoning, so that other experts can follow and validate it. Meet quality standards through iterative feedback and peer review cycles. Required Qualifications (MUST) PhD in Computational Chemistry, Structural Biology, Biophysics, Bioinformatics, Medicinal Chemistry, Biochemistry, or a closely related field. Hands-on research experience in an academic or industry lab (wetlab experience is a plus). Professional written and spoken English (C1 or higher). Preferred Skills Postdoctoral or industry research experience (pharma/biotech) in drug discovery or structural biology. Strong publication record, particularly first-author papers in relevant journals. Molecular modeling and simulation: GROMACS, AMBER, NAMD, OpenMM, free energy methods (FEP/TI). Structure prediction and design: AlphaFold, Rosetta, homology modeling, cryo-EM / X-ray crystallography data interpretation. Docking and virtual screening: AutoDock, Glide, Schrödinger Suite, MOE. Cheminformatics: RDKit, QSAR/QSPR, ADMET prediction, fingerprinting, library design. Proteomics and metabolomics: LC-MS/MS, MaxQuant, DIA/DDA workflows, PTM analysis, untargeted metabolomics. Programming: Python (required in practice), plus R, Bash, or similar; experience with ML for molecular property prediction (GNNs, generative models) is a plus. Experience with benchmarking, model evaluation, or scientific writing/reviewing. Ability to explain complex scientific concepts clearly and precisely in writing.
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Rate, openings and requirements checked 2026-10-19 against micro1's own public postings.