Computational Chemistry, Structural Biology & Drug Discovery Scientist (PhD)
Listing checked October 15, 2026 · pay as published by Micro1
Overview
This contract role puts your computational chemistry and structural biology expertise to work training next-generation AI systems. You will craft expert-level scientific problems, evaluate model outputs for accuracy, and build detailed rubrics grounded in primary literature. The position is fully remote and open worldwide. Your written explanations must be clear enough for other experts to follow and validate.
What You'll Do6
- 1Create challenging, expert-level problems in computational chemistry, structural biology, and drug discovery with clear, verifiable solutions.
- 2Assess AI model outputs for scientific accuracy, rigor, and depth of reasoning, catching subtle errors that non-specialists would miss.
- 3Build detailed rubrics and reference answers based on primary literature and established methodology.
- 4Apply domain knowledge in molecular modeling and simulation, protein structure prediction and design, virtual screening and docking, QSAR/ADMET modeling, and proteomics/metabolomics data analysis.
- 5Write clear explanations of your reasoning so other experts can follow and validate it.
- 6Meet quality standards through iterative feedback and peer review cycles.
Requirements12
- 1PhD in Computational Chemistry, Structural Biology, Biophysics, Bioinformatics, Medicinal Chemistry, Biochemistry, or a closely related field.
- 2Hands-on research experience in an academic or industry lab. Wetlab experience is a plus.
- 3Professional written and spoken English at C1 level or higher.
- 4Postdoctoral or industry research experience in pharma/biotech drug discovery or structural biology is preferred.
- 5Strong publication record, particularly first-author papers in relevant journals.
- 6Molecular modeling and simulation: GROMACS, AMBER, NAMD, OpenMM, free energy methods (FEP/TI).
- 7Structure prediction and design: AlphaFold, Rosetta, homology modeling, cryo-EM / X-ray crystallography data interpretation.
- 8Docking and virtual screening: AutoDock, Glide, Schrödinger Suite, MOE.
- 9Cheminformatics: RDKit, QSAR/QSPR, ADMET prediction, fingerprinting, library design.
- 10Proteomics and metabolomics: LC-MS/MS, MaxQuant, DIA/DDA workflows, PTM analysis, untargeted metabolomics.
- 11Programming: Python required in practice, plus R, Bash, or similar. Experience with ML for molecular property prediction (GNNs, generative models) is a plus.
- 12Experience with benchmarking, model evaluation, or scientific writing/reviewing.
Who Should Apply
The ideal candidate holds a PhD in computational chemistry, structural biology, or a related field and has hands-on lab research experience. You should be comfortable with molecular modeling tools like GROMACS or AMBER, structure prediction methods such as AlphaFold, and cheminformatics libraries like RDKit. Strong written English at C1 level or higher is essential for explaining complex reasoning.
Salary Insight
Compensation for this contract role ranges from $45 to $90 per hour. The final rate is discussed during the hiring process.
Pay and demand for Science & Research roles
AggregatedTypical pay
$85/hour
This role
$45–$90/hr
Most Science & Research roles pay $68–$100 per hour. This role's pay sits below that range.
Based on 58 similar roles that publish pay · 3 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
- Live similar roles
- 70
- Listed in last 30 days
- 25
- Remote
- 97%
Hiring most right now: micro1 (19) · AfterQuery (17) · Mercor (14)
Most requested skills · share of roles
- scientific writing27%
- biochemistry21%
- python20%
- biology19%
Figures from Science & Research roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.
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Compensation
$45–90/hr
Required Skills
Application Tip
Highlight your experience with specific tools mentioned in the preferred skills, such as GROMACS, AlphaFold, or RDKit, and quantify your research impact with metrics like number of first-author publications or successful drug discovery projects.
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