Senior AI Scientist Drug Discovery & Computational Biology
HybridDallas, Texas, United States
Job Summary
Apply artificial intelligence and machine learning methodologies to drug discovery, including predictive modeling, lead optimization, and translational research. Implement graph machine learning techniques for biological networks, molecular property prediction, and target identification. Conduct virtual cell screening and AI-driven target discovery, focusing on rare disease research and therapeutic innovation. Design small molecules and biologics using AI tools for toxicity prediction, off-target assessment, and candidate optimization. Analyze protein structures and integrate structural data into computational workflows to accelerate therapeutic discovery through collaboration with multidisciplinary R&D teams.
Required Qualifications
- Drug Discovery & Computational Biology
- AI and machine learning methodologies for drug discovery, including predictive modeling, lead optimization, and translational research applications
- Graph machine learning techniques for biological networks, molecular property prediction, target identification, and knowledge graph-based discovery
- Virtual cell screening and AI-driven target discovery platforms, with particular focus on rare disease research and therapeutic innovation
- AI-driven molecular design for small molecules and biologics (Abs/VHH), including toxicity prediction, off-target assessment, developability analysis, and candidate optimization
- Structural biology, including protein structure analysis, molecular interactions, computational modeling, and integration of structural data into drug discovery workflows
- A strong track record of leveraging advanced computational approaches to accelerate therapeutic discovery
- The ability to collaborate effectively with multidisciplinary research and development teams
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