Job Description

REQUIREMENTS

PhD, PharmD, DVM, MD, or MS with significant industry experience in:

• Medicinal Chemistry
• Pharmacology
• Toxicology
• Chemical Biology
• Molecular Biology
• Pharmaceutical Sciences
• Biochemistry

3–5+ years of hands-on experience in drug discovery or safety assessment, including:

• Drug discovery programs from target validation through lead optimization
• Structure–activity relationship (SAR) analysis
• Pharmacokinetics (PK) and ADME interpretation
• Toxicology and safety pharmacology studies
• Interpretation of in vitro and in vivo experimental data

Strong expertise in:

• Target biology and mechanism-of-action reasoning
• Dose-response relationships and exposure margins
• Translational interpretation between preclinical and clinical findings
• Toxicity mechanisms such as liver toxicity, cardiovascular liabilities, genotoxicity, or reproductive toxicity
• Evaluating whether safety findings are monitorable, manageable, or program-ending

Experience reviewing primary experimental data and study reports, not only summarized conclusions.

Exceptional attention to scientific accuracy and mechanistic reasoning.

Preferred

• 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/ML tools applied to biomedical research

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 (SAR), 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 (SAR)
  • Pharmacokinetics and ADME reasoning
  • Toxicity mechanisms and 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
  • 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.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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