Pharmacology Expert
Summary
A pharmacology expert reviews and curates drug-related content to train AI models, ensuring accuracy and clinical relevance without requiring prior AI experience.
Role Title: Pharmacology Expert
Role Type: Contractor
Location: Remote
micro1 is engaging Pharmacology Experts to contribute their specialized knowledge to a customer-driven project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Scope of Work
- Review and evaluate pharmacological content for accuracy, clarity, and real-world relevance.
- Develop and curate scenarios, case studies, and datasets related to pharmacokinetics, pharmacodynamics, drug interactions, and therapeutic applications.
- Provide expert feedback on AI-generated responses for pharmacology queries, ensuring scientific rigor and clinical adherence.
- Translate complex pharmacology concepts into accessible information for AI model training purposes.
- Identify gaps or inaccuracies in existing materials and propose data-driven improvements.
- Collaborate with interdisciplinary teams to refine guidelines and datasets in line with the latest pharmacological standards.
- Document methodologies and rationales behind pharmacological decisions and recommendations within project deliverables.
Preferred Qualifications
- Advanced degree (PharmD, PhD, MD, or equivalent) in Pharmacology, Pharmaceutical Sciences, or a closely related field.
- Demonstrated expertise in clinical, molecular, or systems pharmacology.
- Experience authoring, reviewing, or teaching pharmacology-related content in academic, clinical, or industry settings.
- Familiarity with current global guidelines, regulatory standards, and best practices in drug therapy and safety.
- Strong analytical and critical evaluation skills—able to discern nuances in complex pharmacological data.
- Ability to communicate complex scientific ideas clearly and concisely to diverse audiences.
- Previous participation in digital, AI, or data annotation projects is an asset but not required.