What are the responsibilities and job description for the Remote | Drug Discovery Scientists & Toxicology Experts — Up to $100/hr position at 24-MAG?
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
Professionals in this role may contribute to:
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
Ideal Profile
Strong candidates may have:
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.
By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy
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
Professionals in this role may contribute to:
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
Ideal Profile
Strong candidates may have:
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.
By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy
Salary : $70 - $100