Artificial Intelligence (AI) Director (Drug Discovery)

Robert Half

  • Shanghai
  • RMB¥1,500,000 per year
  • Permanent
  • Full-time
  • 1 month ago
  • Apply easily
Job Description:Key ResponsibilitiesStrategic Leadership & Innovation
  • Develop and lead the strategic roadmap for integrating AI applications in biologics discovery and development workflows.
  • Identify and prioritize impactful opportunities to apply AI/ML technologies across the biologics value chain, ensuring alignment with organizational goals.
  • Drive innovation by evaluating and implementing cutting-edge AI technologies, including generative AI, foundation models, and simulation platforms.
  • Establish governance frameworks and best practices for AI model development, validation, and deployment to ensure scientific rigor and regulatory compliance.
Technical Excellence & Model Development
  • Collaborate with biology and R&D teams to optimize and deploy AI/ML models for:
  • Protein design and engineering
  • Antibody discovery and optimization
  • Molecular property prediction
  • Predictive toxicology and safety assessment
  • Target identification and validation
  • Biomarker discovery
  • Lead the development and implementation of generative AI approaches for novel biologics design.
  • Develop robust model validation frameworks, ensuring both accuracy and regulatory readiness.
Cross-Functional Collaboration
  • Foster strong partnerships with medicinal chemistry, computational biology, clinical development, and data science teams.
  • Collaborate with external partners, academic institutions, and technology vendors to keep ahead of advancements in AI capabilities.
  • Act as the primary AI/ML technical advisor to senior leadership for biologics-focused projects.
Data Strategy & Infrastructure
  • Drive the creation of integrated data platforms and pipelines to support AI/ML-driven research initiatives.
  • Maintain high standards of data quality, governance, and accessibility across biologics discovery workflows.
  • Champion the adoption and implementation of FAIR principles (Findable, Accessible, Interoperable, Reusable) for data management.
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Robert Half