About this opportunity
Confidential lists this Computational Chemistry and Drug Discovery Scientist (PhD) opportunity in Northern Virginia, Virginia. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Role Overview
Apply advanced scientific expertise to help train next-generation AI systems using rigorous, real-world work in computational chemistry, structural biology, and drug discovery. You will create and evaluate expert-level scientific materials that strengthen model reasoning, accuracy, and depth.
Key Responsibilities
Design challenging scientific problems in computational chemistry, structural biology, and drug discovery, with clear, verifiable solutions.
Assess AI model outputs for scientific accuracy, rigor, and reasoning quality, including subtle errors that may be missed by non-specialists.
Create detailed scoring rubrics and reference answers based on primary literature and established methodologies.
Apply expertise in molecular modeling and simulation, protein structure prediction and design, virtual screening and docking, QSAR/ADMET modeling, and proteomics or metabolomics data analysis.
Document reasoning clearly so other experts can review and validate the work.
Meet quality standards through iterative feedback and peer-review cycles.
Qualifications
PhD in Computational Chemistry, Structural Biology, Biophysics, Bioinformatics, Medicinal Chemistry, Biochemistry, or a closely related field.
Hands-on academic or industry laboratory research experience. Wet-lab experience is a plus.
Professional written and spoken English at C1 level or higher.
Postdoctoral or pharmaceutical or biotechnology industry research experience in drug discovery or structural biology is preferred.
A strong publication record, particularly first-author papers in relevant journals, is preferred.
Experience with molecular modeling and simulation tools and methods, including GROMACS, AMBER, NAMD, OpenMM, FEP, or TI.
Experience with AlphaFold, Rosetta, homology modeling, or interpretation of cryo-EM or X-ray crystallography data.
Experience with docking and virtual screening tools, including AutoDock, Glide, Schrödinger Suite, or MOE.
Cheminformatics experience, including RDKit, QSAR/QSPR, ADMET prediction, fingerprinting, or library design.
Proteomics or metabolomics experience, including LC-MS/MS, MaxQuant, DIA/DDA workflows, PTM analysis, or untargeted metabolomics.
Python proficiency is required in practice. R, Bash, similar languages, and machine-learning experience for molecular property prediction, including GNNs or generative models, are beneficial.
Experience with benchmarking, model evaluation, scientific writing, or scientific reviewing.
Ability to explain complex scientific concepts precisely and clearly in writing.
Work Terms
Independent contractor engagement.
Remote work is available worldwide.
Compensation
$45 to $90 per hour.
Application
Submit an application and acknowledge the applicable candidate terms and privacy policy.
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.