Job Description
Role Description
We are sharing a specialised part-time consulting opportunity for drug discovery scientists, medicinal chemists, pharmacologists, toxicologists, and related life sciences experts with strong expertise in therapeutic discovery, safety assessment, and translational pharmacology. This role supports collaborations with leading AI research laboratories and AI-driven life sciences partners working to improve advanced biomedical AI systems through scientific dataset review, annotation, mechanistic reasoning validation, and pharmacological interpretation.
Selected professionals will help review and validate scientific datasets, evaluate mechanistic reasoning related to drug discovery and toxicology, interpret complex biological and pharmacological findings, and improve the scientific rigor of next-generation AI systems used in biomedical research.
- Key Responsibilities
- Scientific Data Annotation
- Review and annotate datasets related to drug discovery, pharmacology, and safety biology.
- Interpret experimental outputs from target biology studies, biochemical assays, cellular models, and safety screens.
- Analyze relationships between compound structure, potency, selectivity, exposure, and toxicity signals.
- Identify mechanistic explanations behind efficacy or toxicity findings across discovery experiments.
- Distinguish meaningful biological signal from experimental artifacts, assay interference, or model limitations.
- Quality Review & Validation
- Audit annotated scientific datasets for biological, pharmacological, and safety accuracy.
- Validate structure–activity relationships, target engagement logic, and pharmacokinetic interpretations.
- Evaluate AI-generated reasoning on drug mechanism, toxicity risk, and safety margins.
- Ensure correct interpretation of dose-response relationships, exposure margins, and translational relevance.
- Methodology & Knowledge Contribution
- Contribute to annotation guidelines for drug discovery workflows, structure–activity relationships, pharmacokinetics and ADME reasoning, toxicity mechanisms, safety pharmacology, translational biology, and target validation.
- Provide expertise on how discovery teams balance potency, selectivity, safety, and developability.
- Advise on classification of toxicity findings, safety signals, and risk assessment frameworks.
- Model Evaluation & Feedback
- Review AI-generated reasoning traces involving drug mechanism of action, target biology interpretation, toxicity mechanisms and risk assessment, and pharmacokinetic and exposure modeling.
- Assess whether conclusions logically follow from experimental evidence and biological context.
- Provide structured feedback to improve scientific rigor, causal reasoning, and translational relevance in model outputs.
- Documentation & Training Support
- Contribute to scientific standards documentation and training materials for model development.
- Help define gold-standard examples of drug discovery reasoning and toxicity interpretation.
- Support calibration workflows spanning pharmacology, toxicology, and translational biology domains.
- Qualifications
- PhD, PharmD, DVM, MD, or MS with significant industry experience in Medicinal Chemistry, Pharmacology, Toxicology, Chemical Biology, Molecular Biology, Pharmaceutical Sciences, Biochemistry, or related life sciences fields.
- 3–5+ years of hands-on experience in drug discovery or safety assessment.
- Experience supporting drug discovery programs from target validation through lead optimization.
- Strong experience with structure–activity relationship analysis, pharmacokinetics, ADME interpretation, toxicology, and safety pharmacology studies.
- Ability to interpret in vitro and in vivo experimental data with strong scientific accuracy and mechanistic reasoning.
- Strong expertise in target biology, mechanism-of-action reasoning, dose-response relationships, exposure margins, and translational interpretation between preclinical and clinical findings.
- Experience reviewing primary experimental data and study reports, not only summarized conclusions.
- Exceptional attention to detail and scientific rigor.
- Preferred Qualifications
- Experience in pharmaceutical or biotechnology drug discovery teams.
- Background in lead optimization, translational biology, or nonclinical safety.
- Familiarity with DMPK workflows, safety biomarkers, and regulatory toxicology considerations.
- Experience contributing to cross-functional discovery teams.
- Exposure to AI or machine learning tools applied to biomedical research.
- Why This Opportunity
- Contribute directly to cutting-edge AI research in drug discovery, toxicology, and translational pharmacology.
- Help improve how advanced AI systems reason about therapeutic mechanisms, safety biology, and pharmacological tradeoffs.
- Collaborate with researchers building next-generation biomedical AI models.
- Flexible remote work with competitive compensation.
- Contract Details
- Independent contractor role.
- Fully remote with flexible scheduling.
- Compensation range of $70–$100 per hour.
- Weekly payments via Stripe or Wise.
- Projects may be extended, shortened, or concluded early depending on project needs and performance.
- Work will not involve access to confidential or proprietary information from any employer, client, or institution.
- Please note: We are unable to support H1-B or STEM OPT candidates at this time.
About the Platform
This opportunity is available through a leading AI-driven work platform that connects domain experts with frontier AI research projects. Experts contribute to improving advanced AI systems by providing specialised expertise in biomedical reasoning, scientific annotation, pharmacological interpretation, toxicology review, and translational life sciences evaluation.
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